@inproceedings{hoffmann_hyperparameters_2022,
  author    = {Maximilian Hoffmann and
               Ralph Bergmann},
  editor    = {Mark T. Keane and
               Nirmalie Wiratunga},
  title     = {{Improving Automated Hyperparameter Optimization with Case-Based Reasoning}},
  booktitle = {Case-Based Reasoning Research and Development - 30th International
               Conference, {ICCBR} 2022, Nancy, France, September 12-15, 2022, Proceedings},
  series    = {Lecture Notes in Computer Science},
  volume    = {13405},
  pages     = {273--288},
  publisher = {Springer},
  year      = {2022},
  abstract  = {The hyperparameter configuration of machine learning models has a great influence on their performance. These hyperparameters are often set either manually w. r. t. to the experience of an expert or by an Automated Hyperparameter Optimization (HPO) method. However, integrating experience knowledge into HPO methods is challenging. Therefore, we propose the approach HypOCBR (Hyperparameter Optimization with Case-Based Reasoning) that uses Case-Based Reasoning (CBR) to improve the optimization of hyperparameters. HypOCBR is used as an addition to HPO methods and builds up a case base of sampled hyperparameter vectors with their loss values. The case base is then used to retrieve hyperparameter vectors given a query vector and to make decisions whether to proceed trialing with this query or abort and sample another vector. The experimental evaluation investigates the suitability of HypOCBR for two deep learning setups of varying complexity. It shows its potential to improve the optimization results, especially in complex scenarios with limited optimization time.},
  url = {http://www.wi2.uni-trier.de/shared/publications/2022_ICCBR__Hyperparameter_Optimization_with_CBR.pdf},
  doi       = {10.1007/978-3-031-14923-8\_18}
}

The hyperparameter configuration of machine learning models has a great influence on their performance. These hyperparameters are often set either manually w. r. t. to the experience of an expert or by an Automated Hyperparameter Optimization (HPO) method. However, integrating experience knowledge into HPO methods is challenging. Therefore, we propose the approach HypOCBR (Hyperparameter Optimization with Case-Based Reasoning) that uses Case-Based Reasoning (CBR) to improve the optimization of hyperparameters. HypOCBR is used as an addition to HPO methods and builds up a case base of sampled hyperparameter vectors with their loss values. The case base is then used to retrieve hyperparameter vectors given a query vector and to make decisions whether to proceed trialing with this query or abort and sample another vector. The experimental evaluation investigates the suitability of HypOCBR for two deep learning setups of varying complexity. It shows its potential to improve the optimization results, especially in complex scenarios with limited optimization time.

@inproceedings{hoffmann_gpu_astar_2022,
  author    = {Maximilian Hoffmann and Lukas Malburg and Nico Bach and
               Ralph Bergmann},
  editor    = {Mark T. Keane and
               Nirmalie Wiratunga},
  title     = {{GPU-Based Graph Matching for Accelerating Similarity Assessment in Process-Oriented Case-Based Reasoning}},
  booktitle = {Case-Based Reasoning Research and Development - 30th International Conference, {ICCBR} 2022, Nancy, France, September 12-15, 2022, Proceedings},
  series    = {Lecture Notes in Computer Science},
  abstract  = {In Process-Oriented Case-Based Reasoning (POCBR), determining the similarity between cases represented as semantic graphs often requires some kind of inexact graph matching, which generally is an NP-hard problem. Heuristic search algorithms such as A* search have been successfully applied for this task, but the computational performance is still a limiting factor for large case bases. As related work shows a great potential for accelerating A* search by using GPUs, we propose a novel approach called AMonG for efficiently computing graph similarities with an A* graph matching process involving GPU computing. The three-phased matching process distributes the search process over multiple search instances running in parallel on the GPU. We develop and examine different strategies within these phases that allow to customize the matching process adjusted to the problem situation to be solved. The experimental evaluation compares the proposed GPU-based approach with a pure CPU-based one. The results clearly demonstrate that the GPU-based approach significantly outperforms the CPU-based approach in a retrieval scenario, leading to an average speedup factor of 16.},
  volume    = {13405},
  pages     = {240--255},
  publisher = {Springer},
  doi       = {10.1007/978-3-031-14923-8\_16},
  url = {http://www.wi2.uni-trier.de/shared/publications/2022_ICCBR__A_Star_GPU.pdf},
  year      = {2022}
}

In Process-Oriented Case-Based Reasoning (POCBR), determining the similarity between cases represented as semantic graphs often requires some kind of inexact graph matching, which generally is an NP-hard problem. Heuristic search algorithms such as A* search have been successfully applied for this task, but the computational performance is still a limiting factor for large case bases. As related work shows a great potential for accelerating A* search by using GPUs, we propose a novel approach called AMonG for efficiently computing graph similarities with an A* graph matching process involving GPU computing. The three-phased matching process distributes the search process over multiple search instances running in parallel on the GPU. We develop and examine different strategies within these phases that allow to customize the matching process adjusted to the problem situation to be solved. The experimental evaluation compares the proposed GPU-based approach with a pure CPU-based one. The results clearly demonstrate that the GPU-based approach significantly outperforms the CPU-based approach in a retrieval scenario, leading to an average speedup factor of 16.

@inproceedings{Malburg_AdaptiveWorkflowManagement_2022,
	title = {{Towards Adaptive Workflow Management by Case-Based Reasoning and Automated Planning}},
	author = {Malburg, Lukas and Bergmann, Ralph},
	year = {2022},
	editor    = {Pascal Reuss and Jakob Schönborn},
	booktitle = {{Workshops Proceedings for the Thirtieth International Conference
               on Case-Based Reasoning co-located with the Thirtieth International
               Conference on Case-Based Reasoning {(ICCBR} 2022), Nancy, France,
               September 12-15, 2022}},
	series    = {{CEUR} Workshop Proceedings},
	publisher = {CEUR-WS.org},
	note = {Accepted for Publication.},
	keywords = {{Case-Based Reasoning, Automated Planning, Industry 4.0, Adaptive Workflow Management, Cyber-Physical Workflows}},
	abstract={Adaptive workflow management is an important topic in recent years, as increasing dynamics due to growing customer demands and faster changing market conditions require more flexibility in workflows. This is especially the case for rigid and rather standardized production processes that cannot be easily modified, if, for example, a breakdown occurs in one of the production lines. The goal of the Fourth Industrial Revolution (Industry 4.0), is to provide, among others, more flexible and cost-effective processes in companies by using Artificial Intelligence (AI) methods. In this paper, we present 1) a framework for adaptive workflow management for IoT-enhanced manufacturing processes and 2) an idea for a new adaptation method that combines Case-Based Reasoning (CBR) and automated planning. In this context, we discuss the benefits of such a synergistic combination and introduce the framework and the individual phases according to the 4R (Retrieve, Reuse, Revise, Retain) CBR cycle. In addition, we present our physical factory simulation model that can be used to evaluate the suitability of developed research artifacts.}
}

Adaptive workflow management is an important topic in recent years, as increasing dynamics due to growing customer demands and faster changing market conditions require more flexibility in workflows. This is especially the case for rigid and rather standardized production processes that cannot be easily modified, if, for example, a breakdown occurs in one of the production lines. The goal of the Fourth Industrial Revolution (Industry 4.0), is to provide, among others, more flexible and cost-effective processes in companies by using Artificial Intelligence (AI) methods. In this paper, we present 1) a framework for adaptive workflow management for IoT-enhanced manufacturing processes and 2) an idea for a new adaptation method that combines Case-Based Reasoning (CBR) and automated planning. In this context, we discuss the benefits of such a synergistic combination and introduce the framework and the individual phases according to the 4R (Retrieve, Reuse, Revise, Retain) CBR cycle. In addition, we present our physical factory simulation model that can be used to evaluate the suitability of developed research artifacts.

@inproceedings{Zeyen_myRPA_2022,
	title = {{Towards Experience-based Assistance for Personal Robotic Process Automation by Process-Oriented Case-based Reasoning}},
	author = {Zeyen, Christian and Koch, Rudolf, and Schwarz, Sven and Maus, Heiko and Bergmann, Ralph},
	year = {2022},
	editor    = {Pascal Reuss and Jakob Schönborn},
	booktitle = {{ICCBR POCBR’22: Workshop on Process-Oriented Case-based Reasoning at ICCBR-2022, September 2022, Nancy, France}},
	series    = {{CEUR} Workshop Proceedings},
	publisher = {CEUR-WS.org},
	url = {http://www.wi2.uni-trier.de/shared/publications/2022_ZeyenEtal_myRPA_ICCBR.pdf}
}

@inproceedings{Mathew_FlexiTeams_2022,
	title = {{FlexiTeam: Flexible Team andWork Organization using Process-Oriented Case-Based Reasoning}},
	author = {Mathew, Ditty and Bergmann, Ralph and Weyers, Benjamin and Ellwart, Thomas and Bohrmann, Dominique and Hölzchen, Ericson},
	year = {2022},
	editor    = {Pascal Reuss and Jakob Schönborn},
	booktitle = {{ICCBR POCBR’22: Workshop on Process-Oriented Case-based Reasoning at ICCBR-2022, September 2022, Nancy, France}},
	series    = {{CEUR} Workshop Proceedings},
	publisher = {CEUR-WS.org},
	url = {http://www.wi2.uni-trier.de/shared/publications/2022_Mathewetal_ICCBR.pdf}
}

@inproceedings{Hoffmann.2022_ProGAN,
  author    = {Maximilian Hoffmann and
			   Lukas Malburg and
               Ralph Bergmann},
  editor    = {Andrea Marrella and Barbara Weber},
  title     = {{ProGAN: Toward a Framework for Process Monitoring and Flexibility by Change via Generative Adversarial Networks}},
  booktitle = {Business Process Management Workshops - {BPM} 2021,
               Rome, Italy, September 6 - 10, 2021},
  series    = {Lecture Notes in Business Information Processing},
  volume    = {436},
  pages     = {43--55},
  publisher = {Springer.},
  keywords = {{Business process prediction, Generative Adversarial Networks, Flexibility by change, Process adaptation}},
  year      = {2022},
  url       = {https://doi.org/10.1007/978-3-030-94343-1\_4},
  doi       = {10.1007/978-3-030-94343-1\_4},
  abstract = {Monitoring the state of currently running processes and reacting to deviations during runtime is a key challenge in Business Process Management (BPM). The MAPE-K control loop describes four phases for approaching this challenge: Monitor, Analyze, Plan, Execute. In this paper, we present the ProGAN framework, an idea of an approach for implementing the monitor, analyze, and plan phases of MAPE-K. For this purpose, we leverage a deep learning architecture that builds upon Generative Adversarial Networks (GANs): The discriminator is used for monitoring the process in its environment by using sensor data and for detecting deviations w.r.t. the desired process state (monitor phase). The generator is used afterwards for analyzing the detected deviation and its symptoms as well as for adapting the current process to resolve the deviation and to restore the desired state. Both components are trained together by utilizing each other's feedback in a self-supervised way. We demonstrate the application of our approach for an exemplary scenario in the manufacturing domain.},
  url = {http://www.wi2.uni-trier.de/shared/publications/2022_AI4BPM_HoffmannEtal_ProGAN.pdf},
  note = {The original publication is available at www.springerlink.com}
}

Monitoring the state of currently running processes and reacting to deviations during runtime is a key challenge in Business Process Management (BPM). The MAPE-K control loop describes four phases for approaching this challenge: Monitor, Analyze, Plan, Execute. In this paper, we present the ProGAN framework, an idea of an approach for implementing the monitor, analyze, and plan phases of MAPE-K. For this purpose, we leverage a deep learning architecture that builds upon Generative Adversarial Networks (GANs): The discriminator is used for monitoring the process in its environment by using sensor data and for detecting deviations w.r.t. the desired process state (monitor phase). The generator is used afterwards for analyzing the detected deviation and its symptoms as well as for adapting the current process to resolve the deviation and to restore the desired state. Both components are trained together by utilizing each other's feedback in a self-supervised way. We demonstrate the application of our approach for an exemplary scenario in the manufacturing domain.

@inproceedings{Malburg.2022_AdaptiveManagementByCBRAndPlanning,
  author    = {Lukas Malburg and
               Florian Brand and
               Ralph Bergmann},
  title     = {{Adaptive Management of Cyber-Physical Workflows by Means of Case-Based Reasoning and Automated Planning}},
  booktitle = {Enterprise Design, Operations and Computing Workshops - {EDOC} 2022 International Workshops,
               Bolzano-Bozen, Italy, October 3 - 7, 2022},
  series    = {Lecture Notes in Business Information Processing},
  publisher = {Springer.},
  keywords = {{Case-Based Reasoning, Automated Planning, Industry 4.0, Adaptive Workflow Management, Cyber-Physical Workflows}},
  year      = {2022},
  abstract={Today, it is difficult for companies to react to unforeseen events, e.g., global crises. Highly standardized manufacturing processes are particularly limited in their ability to react flexibly, creating a demand for more advanced workflow management techniques, e.g., extended by artificial intelligence methods. In this paper, we describe how Case-Based Reasoning (CBR) can be combined with automated planning to enhance flexibility in cyber-physical production workflows. We present a compositional adaptation method complemented with generative adaptation to resolve unexpected situations during workflow execution. This synergy is advantageous since CBR provides specific knowledge about already experienced situations, whereas planning assists with general knowledge about the domain. In an experimental evaluation, we show that CBR offers a good basis by reusing cases and by adapting them to better suit the current problem. The combination with automated planning further improves these results and, thus, contributes to enhance the flexibility of cyber-physical workflows.},
  note = {Accepted for Publication.}
}

Today, it is difficult for companies to react to unforeseen events, e.g., global crises. Highly standardized manufacturing processes are particularly limited in their ability to react flexibly, creating a demand for more advanced workflow management techniques, e.g., extended by artificial intelligence methods. In this paper, we describe how Case-Based Reasoning (CBR) can be combined with automated planning to enhance flexibility in cyber-physical production workflows. We present a compositional adaptation method complemented with generative adaptation to resolve unexpected situations during workflow execution. This synergy is advantageous since CBR provides specific knowledge about already experienced situations, whereas planning assists with general knowledge about the domain. In an experimental evaluation, we show that CBR offers a good basis by reusing cases and by adapting them to better suit the current problem. The combination with automated planning further improves these results and, thus, contributes to enhance the flexibility of cyber-physical workflows.

@Article{Hoffmann.2022_GraphEmbeddingPOCBR,
AUTHOR = {Maximilian Hoffmann and Ralph Bergmann},
TITLE = {{Using Graph Embedding Techniques in Process-Oriented Case-Based Reasoning}},
JOURNAL = {Algorithms},
VOLUME = {15},
YEAR = {2022},
NUMBER = {2},
ARTICLE-NUMBER = {27},
URL = {https://www.mdpi.com/1999-4893/15/2/27/pdf},
ISSN = {1999-4893},
ABSTRACT = {Similarity-based retrieval of semantic graphs is a core task of Process-Oriented Case-Based Reasoning (POCBR) with applications in real-world scenarios, e.g., in smart manufacturing. The involved similarity computation is usually complex and time-consuming, as it requires some kind of inexact graph matching. To tackle these problems, we present an approach to modeling similarity measures based on embedding semantic graphs via Graph Neural Networks (GNNs). Therefore, we first examine how arbitrary semantic graphs, including node and edge types and their knowledge-rich semantic annotations, can be encoded in a numeric format that is usable by GNNs. Given this, the architecture of two generic graph embedding models from the literature is adapted to enable their usage as a similarity measure for similarity-based retrieval. Thereby, one of the two models is more optimized towards fast similarity prediction, while the other model is optimized towards knowledge-intensive, more expressive predictions. The evaluation examines the quality and performance of these models in preselecting retrieval candidates and in approximating the ground-truth similarities of a graph-matching-based similarity measure for two semantic graph domains. The results show the great potential of the approach for use in a retrieval scenario, either as a preselection model or as an approximation of a graph similarity measure.},
DOI = {10.3390/a15020027}
}

Similarity-based retrieval of semantic graphs is a core task of Process-Oriented Case-Based Reasoning (POCBR) with applications in real-world scenarios, e.g., in smart manufacturing. The involved similarity computation is usually complex and time-consuming, as it requires some kind of inexact graph matching. To tackle these problems, we present an approach to modeling similarity measures based on embedding semantic graphs via Graph Neural Networks (GNNs). Therefore, we first examine how arbitrary semantic graphs, including node and edge types and their knowledge-rich semantic annotations, can be encoded in a numeric format that is usable by GNNs. Given this, the architecture of two generic graph embedding models from the literature is adapted to enable their usage as a similarity measure for similarity-based retrieval. Thereby, one of the two models is more optimized towards fast similarity prediction, while the other model is optimized towards knowledge-intensive, more expressive predictions. The evaluation examines the quality and performance of these models in preselecting retrieval candidates and in approximating the ground-truth similarities of a graph-matching-based similarity measure for two semantic graph domains. The results show the great potential of the approach for use in a retrieval scenario, either as a preselection model or as an approximation of a graph similarity measure.

@inproceedings{kumar_dependencyretrieval_2022,
	author = {Kumar, Rahol and Schultheis, Alexander and Malburg, Lukas and Hoffmann, Maximilian and Bergmann, Ralph},
	title = {{Considering Inter-Case Dependencies During Similarity-Based Retrieval in Process-Oriented Case-Based Reasoning}},
	year = {2022},
	abstract = {In Case-Based Reasoning (CBR), knowledge gained from previously experienced problem-solving situations is stored as cases that can be used to solve similar upcoming problems. Although these cases act as independent knowledge entities, dependencies between cases are common in real-world scenarios, despite being only rarely considered during case retrieval or other CBR phases. In this paper, we introduce so-called inter-case dependencies, which are considered in the context of Process-Oriented CBR (POCBR). Therefore, we 1) derive requirements that must be satisfied for considering dependencies during the retrieval phase, 2) analyze which knowledge representations are suitable for representing dependencies between cases, and, 3) present our approach for Dependency-Guided Retrieval (DGR) that considers these dependencies between cases during the retrieval phase. In the experimental evaluation, the proposed DGR approach is compared to a regular CBR approach in case retrieval scenarios from the cooking domain. The results demonstrate that the use of the DGR approach leads to significantly reduced times for human problem-solving compared to regular CBR.},
	booktitle = {Proceedings of the 35th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2022, Hutchinson Island, Jensen Beach, Florida, USA},
	url = {http://www.wi2.uni-trier.de/shared/publications/2022_Kumar_FLAIRS.pdf},
	doi = {10.32473/flairs.v35i.130680}
}

In Case-Based Reasoning (CBR), knowledge gained from previously experienced problem-solving situations is stored as cases that can be used to solve similar upcoming problems. Although these cases act as independent knowledge entities, dependencies between cases are common in real-world scenarios, despite being only rarely considered during case retrieval or other CBR phases. In this paper, we introduce so-called inter-case dependencies, which are considered in the context of Process-Oriented CBR (POCBR). Therefore, we 1) derive requirements that must be satisfied for considering dependencies during the retrieval phase, 2) analyze which knowledge representations are suitable for representing dependencies between cases, and, 3) present our approach for Dependency-Guided Retrieval (DGR) that considers these dependencies between cases during the retrieval phase. In the experimental evaluation, the proposed DGR approach is compared to a regular CBR approach in case retrieval scenarios from the cooking domain. The results demonstrate that the use of the DGR approach leads to significantly reduced times for human problem-solving compared to regular CBR.

@article{seiger_process_management_smart_factories_2022,
 author = {Seiger, Ronny and Malburg, Lukas and Weber, Barbara and Bergmann, Ralph},
 year = {2022},
 title = {{Integrating process management and event processing in smart factories: A systems architecture and use cases}},
 pages = {575--592},
 volume = {63},
 abstract = {The developments of new concepts for an increased digitization of manufacturing industries in the context of Industry 4.0 have brought about novel system architectures and frameworks for smart production systems. These range from generic frameworks for Industry 4.0 to domain-specific architectures for Industrial Internet of Things (IIoT). While most of the approaches include a service-based architecture for selective integration with enterprise systems, a close two-way integration of the production control systems and IIoT sensors and actuators with Process-Aware Information Systems (PAIS) on the management level for automation and mining of production processes is rarely discussed. This fusion of Business Process Management (BPM) with IIoT can be mutually beneficial for both research areas, but is still in its infancy. We propose a systems architecture for IIoT that shows how to integrate the low-level hardware components – sensors and actuators – of a smart factory with BPM systems. We discuss the software components and their interactions to address challenges of device encapsulation, integration of sensor events, and interaction with existing BPM systems. This integration is demonstrated within several use cases regarding process modeling, automation and mining for a smart factory model, showing benefits of using BPM technologies to analyze, control, and adapt discrete production processes in IIoT.},
 journal = {{Journal of Manufacturing Systems}},
 url = {http://www.wi2.uni-trier.de/shared/publications/2022_Seiger_JOMS.pdf},
 doi = {10.1016/j.jmsy.2022.05.012}
}

The developments of new concepts for an increased digitization of manufacturing industries in the context of Industry 4.0 have brought about novel system architectures and frameworks for smart production systems. These range from generic frameworks for Industry 4.0 to domain-specific architectures for Industrial Internet of Things (IIoT). While most of the approaches include a service-based architecture for selective integration with enterprise systems, a close two-way integration of the production control systems and IIoT sensors and actuators with Process-Aware Information Systems (PAIS) on the management level for automation and mining of production processes is rarely discussed. This fusion of Business Process Management (BPM) with IIoT can be mutually beneficial for both research areas, but is still in its infancy. We propose a systems architecture for IIoT that shows how to integrate the low-level hardware components – sensors and actuators – of a smart factory with BPM systems. We discuss the software components and their interactions to address challenges of device encapsulation, integration of sensor events, and interaction with existing BPM systems. This integration is demonstrated within several use cases regarding process modeling, automation and mining for a smart factory model, showing benefits of using BPM technologies to analyze, control, and adapt discrete production processes in IIoT.

@article{Grueger.2022_SensorStreamExtension,
  author    = {Joscha Grüger and Lukas Malburg and Jürgen Mangler and Yannis Bertrand and Stefanie Rinderle-Ma and Ralph Bergmann and Estefanía {Serral Asensio}},
  title     = {{SensorStream: An XES Extension for Enriching Event Logs with IoT-Sensor Data}},
  journal   = {CoRR},
  volume    = {abs/2206.11392},
  year      = {2022},
  url       = {https://arxiv.org/abs/2206.11392},
  archivePrefix = {arXiv},
  eprint    = {2206.11392},
  abstract = {Process management and process orchestration/execution are currently hot topics; prevalent trends such as automation and Industry 4.0 require solutions which allow domain-experts to easily model and execute processes in various domains, including manufacturing and health-care. These domains, in turn, rely on a tight integration between hardware and software, i.e. via the Internet of Things (IoT). While process execution is about actuation, i.e. actively triggering actions and awaiting their completion, accompanying IoT sensors monitor humans and the environment. These sensors produce large amounts of procedural, discrete, and continuous data streams, that hold the key to understanding the quality of process subjects (e.g. produced parts), outcome (e.g. quantity and quality), and error causes. Processes constantly evolve in conjunction with their IoT environment. This requires joint storage of data generated by processes, with data generated by the IoT sensors is therefore needed. In this paper, we present an extension of the process log standard format XES, namely SensorStream. SensorStream enables to connect IoT data to process events, as well as a set of semantic annotations to describe the scenario and environment during data collection. This allows to preserve the full context required for data-analysis, so that logs can be analyzed even when scenarios or hardware artifacts are rapidly changing. Through additional semantic annotations, we envision the XES extension log format to be a solid based for the creation of a (semi-)automatic analysis pipeline, which can support domain experts by automatically providing data visualization, or even process insights.}
}

Process management and process orchestration/execution are currently hot topics; prevalent trends such as automation and Industry 4.0 require solutions which allow domain-experts to easily model and execute processes in various domains, including manufacturing and health-care. These domains, in turn, rely on a tight integration between hardware and software, i.e. via the Internet of Things (IoT). While process execution is about actuation, i.e. actively triggering actions and awaiting their completion, accompanying IoT sensors monitor humans and the environment. These sensors produce large amounts of procedural, discrete, and continuous data streams, that hold the key to understanding the quality of process subjects (e.g. produced parts), outcome (e.g. quantity and quality), and error causes. Processes constantly evolve in conjunction with their IoT environment. This requires joint storage of data generated by processes, with data generated by the IoT sensors is therefore needed. In this paper, we present an extension of the process log standard format XES, namely SensorStream. SensorStream enables to connect IoT data to process events, as well as a set of semantic annotations to describe the scenario and environment during data collection. This allows to preserve the full context required for data-analysis, so that logs can be analyzed even when scenarios or hardware artifacts are rapidly changing. Through additional semantic annotations, we envision the XES extension log format to be a solid based for the creation of a (semi-)automatic analysis pipeline, which can support domain experts by automatically providing data visualization, or even process insights.

@article{Malburg.2022_IoTEnrichedEventLog,
  author    = {Lukas Malburg and Joscha Grüger and Ralph Bergmann},
  title     = {{An IoT-Enriched Event Log for Process Mining in Smart Factories}},
  journal   = {CoRR},
  volume    = {abs/2209.02702},
  year      = {2022},
  url       = {https://arxiv.org/abs/2209.02702},
  archivePrefix = {arXiv},
  eprint    = {2209.02702},
  abstract = {Modern technologies such as the Internet of Things (IoT) are becoming increasingly important in various domains, including Business Process Management (BPM) research. One main research area in BPM is process mining, which can be used to analyze event logs, e.g., for checking the conformance of running processes. However, there are only a few IoT-based event logs available for research purposes. Some of them are artificially generated and the problem occurs that they do not always completely reflect the actual physical properties of smart environments. In this paper, we present an IoT-enriched XES event log that is generated by a physical smart factory. For this purpose, we create the SensorStream XES extension for representing IoT-data in event logs. Finally, we present some preliminary analysis and properties of the log.}
}

Modern technologies such as the Internet of Things (IoT) are becoming increasingly important in various domains, including Business Process Management (BPM) research. One main research area in BPM is process mining, which can be used to analyze event logs, e.g., for checking the conformance of running processes. However, there are only a few IoT-based event logs available for research purposes. Some of them are artificially generated and the problem occurs that they do not always completely reflect the actual physical properties of smart environments. In this paper, we present an IoT-enriched XES event log that is generated by a physical smart factory. For this purpose, we create the SensorStream XES extension for representing IoT-data in event logs. Finally, we present some preliminary analysis and properties of the log.

@article{articlegr22,
author = {Grüger, Joscha and Geyer, Tobias and Bergmann, Ralph and Braun, Stephan},
year = {2022},
month = {06},
pages = {359-374},
title = {CGK4PM: Towards a Methodology for the Systematic Generation of Clinical Guideline Process Models and the Utilization of Conformance Checking},
volume = {2},
journal = {BioMedInformatics},
doi = {10.3390/biomedinformatics2030023},
url 		= {https://www.mdpi.com/2673-7426/2/3/23/pdf?version=1656334760}
}

@article{grueger2022,
author = {Grüger, Joscha and Geyer, Tobias and Kuhn, Martin and Braun, StephanA and Bergmann, Ralph},
year = {2022},
month = {01},
pages = {301-313},
title = {Verifying Guideline Compliance in Clinical Treatment Using Multi-perspective Conformance Checking: A Case Study},
isbn = {978-3-030-98580-6},
doi = {10.1007/978-3-030-98581-3_22},
url 		= {https://link.springer.com/content/pdf/10.1007/978-3-030-98581-3.pdf}
}

@INPROCEEDINGS{klein_SiameseNetworkPredM_2021,
  author={Klein, Patrick and Weingarz, Niklas and Bergmann, Ralph},
  booktitle={2021 International Joint Conference on Neural Networks (IJCNN)},
  title={Using Expert Knowledge for Masking Irrelevant Data Streams in Siamese Networks for the Detection and Prediction of Faults},
  year={2021},
  pages={1-10},
  doi={10.1109/IJCNN52387.2021.9533544},
  url={http://www.wi2.uni-trier.de/shared/publications/2021_IJCNN_SiameseNetwork_PredictiveMaintenance.pdf}
}

@article{malburg_objectDetection_2021,
  author    = {Lukas Malburg and Manfred-Peter Rieder and Ronny Seiger and Patrick Klein and Ralph Bergmann},
  title     = {{Object Detection for Smart Factory Processes by Machine Learning}},
  booktitle = {The 4th International Conference on Emerging Data and Industry 4.0 (EDI40), Warsaw, Poland, March 23 - 26, 2021},
  journal    = {Procedia Computer Science},
  volume    = {184},
  pages     = {581--588},
  publisher = {Elsevier.},
  keywords = {{Process Monitoring, Object Detection, Computer Vision, Machine Learning, Industry 4.0, Cyber-Physical Production Systems}},
  year      = {2021},
  url       = {https://doi.org/10.1016/j.procs.2021.04.009},
  doi       = {10.1016/j.procs.2021.04.009},
  abstract={The production industry is in a transformation towards more autonomous and intelligent manufacturing. In addition to more flexible production processes to dynamically respond to changes in the environment, it is also essential that production processes are continuously monitored and completed in time. Video-based methods such as object detection systems are still in their infancy and rarely used as basis for process monitoring. In this paper, we present a framework for video-based monitoring of manufacturing processes with the help of a physical smart factory simulation model. We evaluate three state-of-the-art object detection systems regarding their suitability to detect workpieces and to recognize failure situations that require adaptations. In our experiments, we are able to show that detection accuracies above 90% can be achieved with current object detection methods.},
  url = {http://www.wi2.uni-trier.de/shared/publications/2021_MalburgEtAl_ObjectDetectionInSmartFactories.pdf},
  note = {Best Paper.}
}

The production industry is in a transformation towards more autonomous and intelligent manufacturing. In addition to more flexible production processes to dynamically respond to changes in the environment, it is also essential that production processes are continuously monitored and completed in time. Video-based methods such as object detection systems are still in their infancy and rarely used as basis for process monitoring. In this paper, we present a framework for video-based monitoring of manufacturing processes with the help of a physical smart factory simulation model. We evaluate three state-of-the-art object detection systems regarding their suitability to detect workpieces and to recognize failure situations that require adaptations. In our experiments, we are able to show that detection accuracies above 90% can be achieved with current object detection methods.

@inproceedings{malburg_gpuretrieval_2021,
	author = {Malburg, Lukas and Hoffmann, Maximilian and Trumm, Simon and Bergmann, Ralph},
	title = {{Improving Similarity-Based Retrieval Efficiency by Using Graphic Processing Units in Case-Based Reasoning}},
	year = {2021},
    doi={10.32473/flairs.v34i1.128345},
    url       = {https://doi.org/10.32473/flairs.v34i1.128345},
	abstract = {The accelerated growth of available data causes case bases of increasing sizes and thus lowers efficiency during the case retrieval phase in Case-Based Reasoning (CBR) systems. Even though, many complex and data-intensive tasks are solved by using Graphic Processing Units (GPUs), its application in CBR research has yet to advance past the early stage phase. In this paper, we present an approach to use CUDA-compatible GPUs for similarity assessment of structural, feature vector based cases. Our approach supports several syntactic and semantic similarity measures and is implemented in the open-source case-based reasoning framework ProCAKE. When comparing to current retrieval techniques that calculate similarities on the CPU, our GPU-based approach outperforms them by a factor of up to 37. In addition, our evaluation indicates that the performance gains increase with higher case complexity.},
	booktitle = {Proceedings of the 34th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2021, North Miami Beach, Florida, USA},
	url = {http://www.wi2.uni-trier.de/shared/publications/2021_MalburgEtAl_ImprovingRetrievalByGPUs.pdf},
	note = {Best Student Paper.}
}

The accelerated growth of available data causes case bases of increasing sizes and thus lowers efficiency during the case retrieval phase in Case-Based Reasoning (CBR) systems. Even though, many complex and data-intensive tasks are solved by using Graphic Processing Units (GPUs), its application in CBR research has yet to advance past the early stage phase. In this paper, we present an approach to use CUDA-compatible GPUs for similarity assessment of structural, feature vector based cases. Our approach supports several syntactic and semantic similarity measures and is implemented in the open-source case-based reasoning framework ProCAKE. When comparing to current retrieval techniques that calculate similarities on the CPU, our GPU-based approach outperforms them by a factor of up to 37. In addition, our evaluation indicates that the performance gains increase with higher case complexity.

@article{Hoffmann.2021_InformedMLCBR,
  author    = {Maximilian Hoffmann and
               Ralph Bergmann},
  title     = {Informed Machine Learning for Improved Similarity Assessment in Process-Oriented
               Case-Based Reasoning},
  journal   = {CoRR},
  volume    = {abs/2106.15931},
  year      = {2021},
  url       = {https://arxiv.org/pdf/2106.15931.pdf},
  archivePrefix = {arXiv},
  eprint    = {2106.15931},
  note={Presented at the IJCAI-21 workshop on Deep Learning, Case-Based Reasoning, and AutoML: Present and Future Synergies, Montreal, August 21-26}
}

@inproceedings{Theusch_2021_PHMe,
  title		= {{Fault Detection and Condition Monitoring in District Heating Using Smart Meter Data}},
  author	= {Theusch, Felix and Klein, Patrick and Bergmann, Ralph and Wilke, Wolfgang and Bock, Wolfgang and Weber, Adrian},
  booktitle	= {Proceedings of the European Conference of the PHM Society 2021},
  year		= {2021},
  note		= {Accepted for publication.},
  url 		= {http://www.wi2.uni-trier.de/shared/publications/2021_PHMe_Fault_detection_and_condition_monitoring_in_district_heating_using_smart_meter_data_final.pdf}
}

@inproceedings{schake_2020,
	title = {{A Time-Series Similarity Measure for Case-Based Deviation Management to Support Flexible Workflow Execution}},
	booktitle = {Case-{Based} {Reasoning} {Research} and {Development}: 28th {International} {Conference}, {ICCBR} 2020, {Salamanca}, {Spain}, {June} 8-12, 2020, {Proceedings}},
	publisher = {Springer},
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	editor    = {Watson, Ian and Weber, Rosina},
	author = {Schake, Erik and Grumbach, Lisa and Bergmann, Ralph},
	year = {2020},
	note = {Accepted for publication. The original publication will be available at www.springerlink.com},
	url = {http://www.wi2.uni-trier.de/publications/2020_Case_Retrieval_for_Workflow_Flexibility.pdf}
}

@inproceedings{hoffmann_graph_embedding_2020,
  author    = {Maximilian Hoffmann and
               Lukas Malburg and
               Patrick Klein and
               Ralph Bergmann},
  editor    = {Ian Watson and
               Rosina O. Weber},
  title     = {{Using Siamese Graph Neural Networks for Similarity-Based Retrieval
               in Process-Oriented Case-Based Reasoning}},
  booktitle = {Case-Based Reasoning Research and Development - 28th International
               Conference, {ICCBR} 2020, Salamanca, Spain, June 8-12, 2020, Proceedings},
  series    = {Lecture Notes in Computer Science},
  volume    = {12311},
  pages     = {229--244},
  publisher = {Springer},
  year      = {2020},
  url = {http://www.wi2.uni-trier.de/shared/publications/2020_ICCBR__Workflow_Graph_Embedding.pdf},
  doi       = {10.1007/978-3-030-58342-2\_15},
  abstract = {Similarity-based retrieval of semantic graphs is widely used in
				real-world scenarios, e.g., in the domain of business workflows. To tackle
				the problem of complex and time-consuming graph similarity computations
				during retrieval, the MAC/FAC approach is used in Process-
				Oriented Case-Based Reasoning (POCBR), where similar graphs are extracted
				from a preselected set of candidate graphs. These graphs result
				from a similarity computation with a computationally inexpensive similarity
				measure. The contribution of this paper is a novel similarity measure
				where vector space embeddings generated by two siamese Graph
				Neural Networks (GNNs) are used to approximate the similarities of
				a precise but therefore computationally complex graph similarity measure.
				This includes a special scheme for encoding semantic graphs to be
				used in the neural networks. The evaluation examines the quality and
				performance of these models in preselecting retrieval candidates and in
				approximating the ground-truth similarities of the graph similarity measure.
				The results show great potential of the approach for being used in
				a MAC/FAC scenario, either as a preselection model or as an approximation
				of the graph similarity measure.},
	note = {The original publication is available at www.springerlink.com}
}

Similarity-based retrieval of semantic graphs is widely used in real-world scenarios, e.g., in the domain of business workflows. To tackle the problem of complex and time-consuming graph similarity computations during retrieval, the MAC/FAC approach is used in Process- Oriented Case-Based Reasoning (POCBR), where similar graphs are extracted from a preselected set of candidate graphs. These graphs result from a similarity computation with a computationally inexpensive similarity measure. The contribution of this paper is a novel similarity measure where vector space embeddings generated by two siamese Graph Neural Networks (GNNs) are used to approximate the similarities of a precise but therefore computationally complex graph similarity measure. This includes a special scheme for encoding semantic graphs to be used in the neural networks. The evaluation examines the quality and performance of these models in preselecting retrieval candidates and in approximating the ground-truth similarities of the graph similarity measure. The results show great potential of the approach for being used in a MAC/FAC scenario, either as a preselection model or as an approximation of the graph similarity measure.

@inproceedings{zeyen_astar_2020,
	author    = {Christian Zeyen and
               Ralph Bergmann},
  editor    = {Ian Watson and
               Rosina O. Weber},
  title     = {A*-Based Similarity Assessment of Semantic Graphs},
  booktitle = {Case-Based Reasoning Research and Development - 28th International
               Conference, {ICCBR} 2020, Salamanca, Spain, June 8-12, 2020, Proceedings},
  series    = {Lecture Notes in Computer Science},
  volume    = {12311},
  pages     = {17--32},
  publisher = {Springer},
  year      = {2020},
  doi       = {10.1007/978-3-030-58342-2\_2},
  url = {http://www.wi2.uni-trier.de/shared/publications/2020_ZeyenBergmann_ICCBR.pdf},
  note = {The original publication is available at www.springerlink.com}
}

@inProceedings{klein_SiameseNN4PredM_2020,
  author    = {Patrick Klein and
               Niklas Weingarz and
               Ralph Bergmann},
  title     = {{Enhancing Siamese Neural Networks through Expert Knowledge for Predictive Maintenance}},
  booktitle = {{IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning}},
  series    = {Communications in Computer and Information Science},
  volume    = {1325},
  %pages    = {1--16},
  publisher = {Springer International Publishing.},
  keywords 	= {{Siamese Neural Network, Predictive Maintenance, Expert Knowledge, 2D Convolution, Time Series Similarity}},
  year      = {2020},
  abstract	={The data provided by cyber-physical production systems (CPPSs) to monitor their condition via data-driven predictive maintenance is often high dimensional and only a few fault and failure (FaF) examples are available. These FaFs can usually be detected in a (small) localized subset of data streams, whereas the use of all data streams induces noise that could negatively affect the training and prediction performance. In addition, a CPPS often consists of multiple similar units that generate comparable data streams and show similar failure modes. However, existing approaches for learning a similarity measure generally do not consider these two aspects. For this reason, we propose two approaches for integrating expert knowledge about class or failure mode dependent attributes into siamese neural networks (SNN). Additionally, we present an attribute-wise encoding of time series based on 2D convolutions. This enables that learned knowledge in the form of filters is shared between similar data streams, which would not be possible with conventional 1D convolutions due to their spatial focus. We evaluate our approaches against state-of-the-art time series similarity measures such as dynamic time warping, NeuralWarp, as well as a feature-based representation approach. Our results show that the integration of expert knowledge is advantageous and combined with the novel SNN architecture it is possible to achieve the best performance compared to the other investigated methods..},
  doi       = {10.1007/978-3-030-66770-2\_6},
  isbn		={978-3-030-66769-6},
  year      = {2020},
  url 		= {http://www.wi2.uni-trier.de/shared/publications/2020_ECML-IoTStreams_SiameseNeuralNetwork-for-PredictiveMaintenance_Preprint.pdf},
  note 		= {The original publication is available at www.springerlink.com}
}

The data provided by cyber-physical production systems (CPPSs) to monitor their condition via data-driven predictive maintenance is often high dimensional and only a few fault and failure (FaF) examples are available. These FaFs can usually be detected in a (small) localized subset of data streams, whereas the use of all data streams induces noise that could negatively affect the training and prediction performance. In addition, a CPPS often consists of multiple similar units that generate comparable data streams and show similar failure modes. However, existing approaches for learning a similarity measure generally do not consider these two aspects. For this reason, we propose two approaches for integrating expert knowledge about class or failure mode dependent attributes into siamese neural networks (SNN). Additionally, we present an attribute-wise encoding of time series based on 2D convolutions. This enables that learned knowledge in the form of filters is shared between similar data streams, which would not be possible with conventional 1D convolutions due to their spatial focus. We evaluate our approaches against state-of-the-art time series similarity measures such as dynamic time warping, NeuralWarp, as well as a feature-based representation approach. Our results show that the integration of expert knowledge is advantageous and combined with the novel SNN architecture it is possible to achieve the best performance compared to the other investigated methods..

@inproceedings{malburg_SemanticWebServices_2020,
  author    = {Lukas Malburg and
               Patrick Klein and
               Ralph Bergmann},
  title     = {{Semantic Web Services for AI-Research with Physical Factory Simulation Models in Industry 4.0}},
  editor    = {Herv{\'{e}} Panetto and
               Kurosh Madani and
               Alexander V. Smirnov},
  booktitle = {Proceedings of the International Conference on Innovative Intelligent
               Industrial Production and Logistics, {IN4PL} 2020, Budapest, Hungary,
               November 2-4, 2020},
  pages     = {32--43},
  publisher = {{SCITEPRESS.}},
  keywords = {{Semantic Web Services, Industry 4.0, Artificial Intelligence, Flexible Cyber-Physical Workflows, OWL-S, WSMO}},
  year      = {2020},
  abstract={The transition to Industry 4.0 requires smart manufacturing systems that are easily configurable and provide a high level of flexibility during manufacturing in order to achieve mass customization or to support cloud manufacturing. To realize this, Cyber-Physical Systems (CPSs) combined with Artificial Intelligence (AI) methods find their way into manufacturing shop floors. For using AI methods in the context of Industry 4.0, semantic web services are indispensable to provide a reasonable abstraction of the underlying manufacturing capabilities. In this paper, we present semantic web services for AI-based research with physical factory simulation models in Industry 4.0. Therefore, we developed 68 semantic web services based on Web Ontology Language for Web Services (OWL-S) and Web Service Modeling Ontology (WSMO) and linked them to an already existing domain ontology for intelligent manufacturing control. Suitable for the requirements of CPS environments, our pre- and postconditions are verified in near real-time by invoking other semantic web services in contrast to complex reasoning within the knowledge base. Finally, we evaluate our implementation by executing a cyber-physical workflow composed of semantic web services using a state-of-the-art workflow management system.},
  doi={10.5220/0010135900320043},
  pages={32-43},
  isbn={978-989-758-476-3},
  url = {http://www.wi2.uni-trier.de/shared/publications/2020_IN4PL_Semantic_Web_Services_MalburgEtAl.pdf}
}

The transition to Industry 4.0 requires smart manufacturing systems that are easily configurable and provide a high level of flexibility during manufacturing in order to achieve mass customization or to support cloud manufacturing. To realize this, Cyber-Physical Systems (CPSs) combined with Artificial Intelligence (AI) methods find their way into manufacturing shop floors. For using AI methods in the context of Industry 4.0, semantic web services are indispensable to provide a reasonable abstraction of the underlying manufacturing capabilities. In this paper, we present semantic web services for AI-based research with physical factory simulation models in Industry 4.0. Therefore, we developed 68 semantic web services based on Web Ontology Language for Web Services (OWL-S) and Web Service Modeling Ontology (WSMO) and linked them to an already existing domain ontology for intelligent manufacturing control. Suitable for the requirements of CPS environments, our pre- and postconditions are verified in near real-time by invoking other semantic web services in contrast to complex reasoning within the knowledge base. Finally, we evaluate our implementation by executing a cyber-physical workflow composed of semantic web services using a state-of-the-art workflow management system.

@inproceedings{grueger20,
        title = {{Process Mining for Case Acquisition in
Oncology: A Systematic Literature Review}},
        author = {Grüger, Joscha and Bergmann, Ralph and Kazik, Yavuz and Kuhn, Martin},
        booktitle={Proceedings of the LWDA 2020 Workshops:
KDML, FGWM, FGWI-BIA, and FGDB},
        pages = {162--173},
        publisher = {CEUR-WS.org},
        year = {2020},
        url = {http://www.wi2.uni-trier.de/shared/publications/2020_PM4HC.pdf}
}

@inproceedings{dietrich20,
        title = {{INWEND}: {Using} {CBR} to automate legal assessment in the context of the {EU} {General} {Data} {Protection} {Regulation}},
        author = {Dietrich, Clarissa and Schriml, Sebastian and Bergmann, Ralph and Raue, Benjamin},
        booktitle={Proceedings of the LWDA 2020 Workshops:
KDML, FGWM, FGWI-BIA, and FGDB},
        pages = {192--201},
        publisher = {CEUR-WS.org},
        year = {2020},
        url = {http://www.wi2.uni-trier.de/shared/publications/2020_INWEND.pdf}
}

@inproceedings{malburg_BPMResearch_2020,
  author    = {Lukas Malburg and
               Ronny Seiger and
               Ralph Bergmann and
			   Barbara Weber},
  editor    = {Adela del-Río-Ortega and Henrik Leopold and Flavia M. Santoro},
  title     = {{Using Physical Factory Simulation Models for Business Process Management Research}},
  booktitle = {Business Process Management Workshops - {BPM} 2020 International Workshops,
               Sevilla, Spain, September 13 - 18, 2020},
  series    = {Lecture Notes in Business Information Processing},
  volume    = {397},
  pages     = {95--107},
  publisher = {Springer},
  keywords = {{Cyber-Physical Production Systems, Factory Simulation Models, Business Process Management, Industry 4.0, Digital Twins}},
  year      = {2020},
  url       = {https://doi.org/10.1007/978-3-030-66498-5\_8},
  doi       = {10.1007/978-3-030-66498-5\_8},
  abstract={The production and manufacturing industries are currently transitioning towards more autonomous and intelligent production lines within the Fourth Industrial Revolution (Industry 4.0). Learning Factories as small scale physical models of real shop floors are realistic platforms to conduct research in the smart manufacturing area without depending on expensive real world production lines or completely simulated data. In this work, we propose to use learning factories for conducting research in the context of Business Process Management (BPM) and Internet of Things (IoT) as this combination promises to be mutually beneficial for both research areas. We introduce our physical Fischertechnik factory models simulating a complex production line and three exemplary use cases of combining BPM and IoT, namely the implementation of a BPM abstraction stack on top of a learning factory, the experience-based adaptation and optimization of manufacturing processes, and the stream processing-based conformance checking of IoT-enabled processes.},
  url = {http://www.wi2.uni-trier.de/shared/publications/2020_MalburgEtAl_BPM.pdf},
  note = {The original publication is available at www.springerlink.com}
}

The production and manufacturing industries are currently transitioning towards more autonomous and intelligent production lines within the Fourth Industrial Revolution (Industry 4.0). Learning Factories as small scale physical models of real shop floors are realistic platforms to conduct research in the smart manufacturing area without depending on expensive real world production lines or completely simulated data. In this work, we propose to use learning factories for conducting research in the context of Business Process Management (BPM) and Internet of Things (IoT) as this combination promises to be mutually beneficial for both research areas. We introduce our physical Fischertechnik factory models simulating a complex production line and three exemplary use cases of combining BPM and IoT, namely the implementation of a BPM abstraction stack on top of a learning factory, the experience-based adaptation and optimization of manufacturing processes, and the stream processing-based conformance checking of IoT-enabled processes.

@misc{
DBWLLOBS2020preprint,
author    = { Lorik Dumani and Manuel Biertz and Alex Witry and Anna-Katharina Ludwig and Mirko Lenz and Stefan Ollinger and Ralph Bergmann and Ralf Schenkel
},
  title     = {The ReCAP Corpus: A Corpus of Complex Argument Graphs on German Education Politics},
  journal   = {CoRR},
  year      = {2020},
  url       = {https://www.uni-trier.de/fileadmin/fb4/prof/INF/DBI/Publikationen/preprint_dumani_corpus.pdf}
}

@misc{ollinger2020stance,
    title={Same Side Stance Classification Task: Facilitating Argument Stance Classification by Fine-tuning a BERT Model},
    author={Stefan Ollinger and Lorik Dumani and Premtim Sahitaj and Ralph Bergmann and Ralf Schenkel},
    year={2020},
    eprint={2004.11163},
    archivePrefix={arXiv},
    primaryClass={cs.CL},
		url = {https://arxiv.org/abs/2004.11163}
}

@article{bergmann2020_DBSpek,
  title={The ReCAP Project -- Similarity Methods for Finding Arguments and Argument Graphs},
  author={Ralph Bergmann and Manuel Biertz and Lorik Dumani and Mirko Lenz and Anna-Katharina Ludwig and Patrick J. Neumann and Stefan Ollinger and Premtim Sahitaj and Ralf Schenkel and Alex Witry},
  journal={Datenbank-Spektrum},
  year={2020},
  publisher={Springer},
	note={Accepted for publication.}
}

@article{althoff2020AIMag,
  title={The 27th International Conference on Case-Based Reasoning},
  author={Althoff, Klaus-Dieter and Bach, Kerstin and Bergmann, Ralph and Marling, Cindy},
  journal={AI Magazine},
  volume={41},
  number={1},
  pages={101--102},
  year={2020}
}

@inproceedings{DBLP:conf/bpm/Maletzki19,
  author    = {Maletzki, Carsten and Rietzke, Eric and Grumbach, Lisa and
               Bergmann, Ralph and
               Kuhn, Norbert},
  title     = {{Utilizing Ontology-Based Reasoning to Support the Execution of Knowledge-Intensive Processes}},
  url = {http://www.wi2.uni-trier.de/publications/2019-AI4BPM-Utilizing-ODD-BP.pdf},
  booktitle = {Business Process Management Workshops - {BPM} 2019 International Workshops},
  year      = {2019}
}

@inproceedings{zeyen_scientificWF_adaptation_2019,
	title = {{Adaptation of Scientific Workflows by Means of Process-Oriented Case-Based Reasoning}},
	editor    = {Kerstin Bach and
               Cindy Marling},
	booktitle = {Case-{Based} {Reasoning} {Research} and {Development}: 27th {International} {Conference}, {ICCBR} 2019, {Otzenhausen}, {Germany}, {September} 8-12, 2019, {Proceedings}},
	publisher = {Springer},
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	author = {Zeyen, Christian and Malburg, Lukas and Bergmann, Ralph},
	year = {2019},
	keywords = {{Process-Oriented Case-Based Reasoning, Workflow Adaptation, Scientific Workflows}},
	abstract = {This paper investigates automatic adaptation of scientific workflows in process-oriented case-based
				reasoning with the goal of providing modeling assistance. With regard to our previous work on the
				adaptation of business workflows, we discuss the differences between the workflow types and the
				implications for transferring the approaches to scientific workflows. An experimental evaluation with
				RapidMiner workflows demonstrates that the approaches can significantly improve workflows towards a
				given query while mostly maintaining their executability and semantic correctness.},
	pages     = {388--403},
	year      = {2019},
	crossref  = {DBLP:conf/iccbr/2019},
	url       = {https://doi.org/10.1007/978-3-030-29249-2\_26},
	doi       = {10.1007/978-3-030-29249-2\_26},
	note = {The original publication is available at www.springerlink.com},
	url = {http://www.wi2.uni-trier.de/shared/publications/2019_ZeyenMalburgBergmann_ICCBR.pdf},
}

This paper investigates automatic adaptation of scientific workflows in process-oriented case-based reasoning with the goal of providing modeling assistance. With regard to our previous work on the adaptation of business workflows, we discuss the differences between the workflow types and the implications for transferring the approaches to scientific workflows. An experimental evaluation with RapidMiner workflows demonstrates that the approaches can significantly improve workflows towards a given query while mostly maintaining their executability and semantic correctness.

@inproceedings{block_ArgGrapSimilarity_2019,
     title = {{Clustering of Argument Graphs Using Semantic Similarity Measures}},
     booktitle = {{KI} 2019: Advances in {Artificial Intelligence}: 42nd {German} {Conference} on {AI}, {Kassel}, {Germany}, {September} 23–26, 2019, {Proceedings}},
     publisher = {Springer},
     author = {Block, Karsten and Trumm, Simon and Sahitaj, Premtim and Ollinger, Stefan and Bergmann, Ralph},
     year = {2019},
     keywords = {{Argumentation, Argument graph similarity, Semantic textual similarity, Text clustering}},
     abstract = {Research on argumentation in Artificial Intelligence recently investigates new methods that contribute to
				the vision of developing robust argumentation machines. One line of research explores ways of reasoning
				with natural language arguments coming from information sources on the web as a foundation for the
				deliberation and synthesis of arguments in specific domains. This paper builds upon arguments represented
				as argument graphs in the standardized Argument Interchange Format. While previous work was focused
				on the development of semantic similarity measures used for the case-based retrieval of argument graphs,
				this paper addresses the problem of clustering argument graphs to explore structures that facilitate
				argumentation interpretation. We propose a k-medoid and an agglomerative clustering approach based on
				semantic similarity measures. We compare the clustering results based on a graph-based semantic measure
				that takes the structure of the argument into account with a semantic word2vec measure on the pure textual
				argument representation. Experiments based on the Microtext corpus show that the graph-based similarity
				is best on internal evaluation measures, while the pure textual measure performs very well for identifying
				topic-specific clusters.},
     note = {Accepted for publication. The original publication will be
			available at www.springerlink.com},
     url = {http://www.wi2.uni-trier.de/shared/publications/2019_BlockTrummSahitajOllingerBergmann_KI.pdf},
}

Research on argumentation in Artificial Intelligence recently investigates new methods that contribute to the vision of developing robust argumentation machines. One line of research explores ways of reasoning with natural language arguments coming from information sources on the web as a foundation for the deliberation and synthesis of arguments in specific domains. This paper builds upon arguments represented as argument graphs in the standardized Argument Interchange Format. While previous work was focused on the development of semantic similarity measures used for the case-based retrieval of argument graphs, this paper addresses the problem of clustering argument graphs to explore structures that facilitate argumentation interpretation. We propose a k-medoid and an agglomerative clustering approach based on semantic similarity measures. We compare the clustering results based on a graph-based semantic measure that takes the structure of the argument into account with a semantic word2vec measure on the pure textual argument representation. Experiments based on the Microtext corpus show that the graph-based similarity is best on internal evaluation measures, while the pure textual measure performs very well for identifying topic-specific clusters.

@inproceedings{klein_workflow_embedding_2019,
	title = {{Learning Workflow Embeddings to Improve the Performance of Similarity-Based Retrieval for Process-Oriented Case-Based Reasoning}},
	editor    = {Kerstin Bach and
               Cindy Marling},
	booktitle = {Case-{Based} {Reasoning} {Research} and {Development}: 27th {International} {Conference}, {ICCBR} 2019, {Otzenhausen}, {Germany}, {September} 8-12, 2019, {Proceedings}},
	publisher = {Springer.},
	author = {Klein, Patrick and Malburg, Lukas and Bergmann, Ralph},
	year = {2019},
	keywords = {{Process-Oriented Case-Based Reasoning, MAC/FAC Retrieval, Graph Embeddings}},
	abstract = {In process-oriented case-based reasoning, similarity-based retrieval of workflow cases from large case
				bases is still a difficult issue due to the computationally expensive similarity assessment. The two-phase
				MAC/FAC (“Many are called, but few are chosen") retrieval has been proven useful to reduce the retrieval
				time but comes at the cost of an additional modeling effort for implementing the MAC phase. In this paper,
				we present a new approach to implement the MAC phase for POCBR retrieval, which makes use of the
				StarSpace embedding algorithm to automatically learn a vector representation for workflows, which can be
				used to significantly speed-up the MAC retrieval phase. In an experimental evaluation in the domain of
				cooking workflows, we show that the presented approach outperforms two existing MAC/FAC approaches
				on the same data.},
	pages     = {188--203},
	year      = {2019},
	url       = {https://doi.org/10.1007/978-3-030-29249-2\_13},
	doi       = {10.1007/978-3-030-29249-2\_13},
	note = {The original publication is available at www.springerlink.com},
	url = {http://www.wi2.uni-trier.de/shared/publications/2019_KleinMalburgBergmann_ICCBR.pdf},
}

In process-oriented case-based reasoning, similarity-based retrieval of workflow cases from large case bases is still a difficult issue due to the computationally expensive similarity assessment. The two-phase MAC/FAC (“Many are called, but few are chosen") retrieval has been proven useful to reduce the retrieval time but comes at the cost of an additional modeling effort for implementing the MAC phase. In this paper, we present a new approach to implement the MAC phase for POCBR retrieval, which makes use of the StarSpace embedding algorithm to automatically learn a vector representation for workflows, which can be used to significantly speed-up the MAC retrieval phase. In an experimental evaluation in the domain of cooking workflows, we show that the presented approach outperforms two existing MAC/FAC approaches on the same data.

@inproceedings{bergmann_proCAKE_demo_2019,
	title = {{ProCAKE: A Process-Oriented Case-Based Reasoning Framework}},
	author = {Bergmann, Ralph and Grumbach, Lisa and Malburg, Lukas and Zeyen, Christian},
	year = {2019},
	editor    = {Stelios Kapetanakis and
               Hayley Borck},
	booktitle = {{Workshops Proceedings for the Twenty-seventh International Conference
               on Case-Based Reasoning co-located with the Twenty-seventh International
               Conference on Case-Based Reasoning {(ICCBR} 2019), Otzenhausen, Germany,
               September 8-12, 2019}},
	series    = {{CEUR} Workshop Proceedings},
	volume    = {2567},
	pages     = {156--161},
	publisher = {CEUR-WS.org},
	keywords = {{Knowledge Management, Process Management, Case-Based Reasoning}},
	abstract={This paper presents ProCAKE -- the process-oriented case-based knowledge engine of the CAKE framework, which has evolved from several research projects at the University of Trier over the years. ProCAKE constitutes a domain-independent framework that can be used to implement diverse structural or process-oriented case-based reasoning applications for integrated process and knowledge management. This paper gives an overview of the main components and demonstrates their application by examples.},
	url = {http://www.wi2.uni-trier.de/shared/publications/2019_BergmannGrumbachMalburgZeyen_ICCBR_Demo.pdf},
}

This paper presents ProCAKE – the process-oriented case-based knowledge engine of the CAKE framework, which has evolved from several research projects at the University of Trier over the years. ProCAKE constitutes a domain-independent framework that can be used to implement diverse structural or process-oriented case-based reasoning applications for integrated process and knowledge management. This paper gives an overview of the main components and demonstrates their application by examples.

@inproceedings{klein_ftonto_2019,
	title = {{FTOnto: A Domain Ontology for a Fischertechnik Simulation Production Factory by Reusing Existing Ontologies}},
	author = {Klein, Patrick and Malburg, Lukas and Bergmann, Ralph},
	  editor    = {Robert J{\"{a}}schke and
               Matthias Weidlich},
	booktitle = {Proceedings of the Conference on "Lernen, Wissen, Daten, Analysen",
               Berlin, Germany, September 30 - October 2, 2019.},
	series    = {{CEUR} Workshop Proceedings},
	volume    = {2454},
	pages     = {253--264},
	publisher = {CEUR-WS.org},
	keywords = {{Ontology Engineering, Industry 4.0, Simulation Factory, Fischertechnik}},
	year      = {2019},
	abstract={Nowadays, semantic information provided by an ontology is indispensable in the context of Industry 4.0, especially when using methods from Artificial Intelligence. The currently available ontologies do not satisfy the demands of simulation environments used for research purposes. For this reason, we develop an ontology customized to Fischertechnik simulation factories by reusing existing ontologies. The ontology has been created according to requirements from two use cases. In our evaluation, it is determined that the ontology is suitable to represent machine components and their relationships while satisfying the specified requirements.},
	url = {http://www.wi2.uni-trier.de/shared/publications/2019_KleinMalburgBergmann_LWDA.pdf}
}

Nowadays, semantic information provided by an ontology is indispensable in the context of Industry 4.0, especially when using methods from Artificial Intelligence. The currently available ontologies do not satisfy the demands of simulation environments used for research purposes. For this reason, we develop an ontology customized to Fischertechnik simulation factories by reusing existing ontologies. The ontology has been created according to requirements from two use cases. In our evaluation, it is determined that the ontology is suitable to represent machine components and their relationships while satisfying the specified requirements.

@inproceedings{lenz_argretrieval_2019,
	title = {{Semantic Textual Similarity Measures for Case-Based Retrieval of Argument Graphs}},
	editor    = {Kerstin Bach and
               Cindy Marling},
	booktitle = {Case-{Based} {Reasoning} {Research} and {Development}: 27th {International} {Conference}, {ICCBR} 2019, {Otzenhausen}, {Germany}, {September} 8-12, 2019, {Proceedings}},
	publisher = {Springer.},
	author = {Lenz, Mirko and Ollinger, Stefan and Sahitaj, Premtim and Bergmann, Ralph},
	year = {2019},
	pages     = {219--234},
	year      = {2019},
	url       = {http://www.wi2.uni-trier.de/shared/publications/2019_LenzOllingerSahitajBergmann_ICCBR.pdf},
	doi       = {10.1007/978-3-030-29249-2\_15},
	note = {The original publication is available at www.springerlink.com}
}

@inproceedings{klein_complexdatagen_2019,
	author={Klein, Patrick and Bergmann, Ralph},
	title={{Generation of Complex data for AI-Based Predictive Maintenance Research With a Physical Factory Model}},
	booktitle={16th {International} {Conference} on {Informatics} in {Control} {Automation} and {Robotics}, {ICINCO} 2019, {Prague}, {Czech} {Republic}, {Proceedings} },
	year={2019},
	pages={40-50},
	volume = {1},
	publisher={SciTePress.},
	organization={INSTICC},
	doi={10.5220/0007830700400050},
	isbn={978-989-758-380-3},
	url={http://www.wi2.uni-trier.de/shared/publications/2019_KleinBergmann_Predictive_Maintenance_data_generation_machine_learning.pdf}
}

@inproceedings{bergmann_argretrieval_2019,
	author = {Bergmann, Ralph and Lenz, Mirko and Ollinger, Stefan and Pfister, Maximilian},
	title = {{Similarity Measures for Case-Based Retrieval of Natural Language Argument Graphs in Argumentation Machines}},
	year = {2019},
	booktitle = {Proceedings of the 32nd Intert. Florida Art. Int. Research Society Conf., FLAIRS 2019, Sarasota, Florida, USA},
	publisher = {AAAI-Press},
	url = {http://www.wi2.uni-trier.de/shared/publications/2019_Bergmann_FLAIRS.pdf},
}

@inproceedings{DBLP:conf/lwa/GrumbachB19,
  author    = {Grumbach, Lisa and Bergmann, Ralph},
  title     = {{Towards Case-Based Deviation Management for Flexible Workflows}},
  booktitle = {Proceedings of the Conference "Lernen, Wissen, Daten, Analysen", {LWDA}
               2019, Berlin, Germany, September 30 - October 2, 2019.},
  year      = {2019},
  url		= {http://www.wi2.uni-trier.de/shared/publications/2019_GrumbachBergmann_LWDA.pdf}
}

@article{Grumbach.2019,
 author = {Grumbach, Lisa and Bergmann, Ralph},
 year = {2019},
 title = {{SEMAFLEX: A novel approach for implementing workflow flexibility by deviation based on constraint satisfaction problem solving}},
 volume = {34},
 number = {4},
 issn = {02664720},
 journal = {Expert Systems},
 doi = {10.1111/exsy.12385}
}

@inproceedings{DBLP:conf/lwa/RietzkeBK19,
  author    = {Eric Rietzke and
               Ralph Bergmann and
               Norbert Kuhn},
  editor    = {Robert J{\"{a}}schke and
               Matthias Weidlich},
  title     = {{ODD-BP} - an Ontology- and Data-Driven Business Process Model},
  booktitle = {Proceedings of the Conference on "Lernen, Wissen, Daten, Analysen",
               Berlin, Germany, September 30 - October 2, 2019},
  series    = {{CEUR} Workshop Proceedings},
  volume    = {2454},
  pages     = {310--321},
  publisher = {CEUR-WS.org},
  year      = {2019},
  url       = {http://ceur-ws.org/Vol-2454/paper\_43.pdf},
}

@inproceedings{grumbach_semanas_2018,
	series = {{CEUR} {Workshop} {Proceedings}},
	title = {{SEMANAS} - {Semantic} {Support} for {Grant} {Application} {Processes}},
	url = {http://www.wi2.uni-trier.de/publications/2018_GrumbachEtAl_LWDA.pdf},
	booktitle = {Lernen. {Wissen}. {Daten}. {Analysen}. ({LWDA} 2018)},
	author = {Grumbach, Lisa and Rietzke, Eric and Schwinn, Markus and Bergmann, Ralph and Kuhn, Norbert},
	year = {2018}
}

@inproceedings{zeyen_nutrients_2018,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {{Considering Nutrients during the Generation of Recipes by Process-Oriented Case-based Reasoning}},
	url = {http://www.wi2.uni-trier.de/shared/publications/2018_ZeyenHoffmannMuellerBergmann_ICCBR.pdf},
	booktitle = {Case-{Based} {Reasoning} {Research} and {Development}: 26th {International} {Conference}, {ICCBR} 2018, {Stockholm}, {Sweden}, {July} 9-12, 2018, {Proceedings}},
	publisher = {Springer},
	author = {Zeyen, Christian and Hoffmann, Maximilian and M{\"u}ller, Gilbert and Bergmann, Ralph},
	editor = {Cox, Michael T. and Funk, Peter and Begum, Shahina},
	year = {2018},
	volume    = {11156},
	pages     = {464--479},
	note = {The original publication is available at www.springerlink.com}
}

@inproceedings{DBLP:conf/inf-dh/LebherzZHBTBHM18,
  author    = {Daniel S. Lebherz and
               Christian Zeyen and
               Jan Hess and
               Ralph Bergmann and
               Ingo J. Timm and
               Thomas Burch and
               Vera Hildenbrandt and
               Claudine Moulin},
  editor    = {Manuel Burghardt and
               Claudia M{\"{u}}ller{-}Birn},
  title     = {Towards Scientific Workflows and Computer Simulation as a Method in
               Digital Humanities},
  booktitle = {GI-Workshop: Im Spannungsfeld zwischen Tool-Building und Forschung
               auf Augenh{\"{o}}he - Informatik und die Digital Humanities,
               {INF-DH} 2018, 25.9.2018, Berlin, Germany},
  publisher = {Gesellschaft f{\"{u}}r Informatik e.V.},
  year      = {2018},
  url = {http://www.wi2.uni-trier.de/shared/publications/2018_Lebherz_INF-DH.pdf},
}

@inproceedings{zeyen_interactive_short_2018,
	publisher = {CEUR-WS.org},
	title = {{Towards an Interactive Workflow Modeling Assistance by Means of Case-Based Reasoning}},
	url = {http://www.wi2.uni-trier.de/publications/2018_ZeyenBergmann_LWDA.pdf},
	booktitle = {Proceedings of the Conference "Lernen, Wissen, Daten, Analysen", {LWDA} 2018},
	author = {Zeyen, Christian and Bergmann, Ralph},
	series    = {{CEUR} Workshop Proceedings},
	volume    = {2191},
	pages     = {355--360},
	year = {2018}
}

@inproceedings{klein_data_generation_2018,
	publisher = {CEUR-WS.org},
	title = {{Data Generation with a Physical Model to Support Machine Learning Research for Predictive Maintenance}},
	url = {http://www.wi2.uni-trier.de/publications/2018_KleinBergmann_LWDA.pdf},
	booktitle = {Proceedings of the Conference "Lernen, Wissen, Daten, Analysen", {LWDA} 2018},
	author = {Klein, Patrick and Bergmann, Ralph},
	volume    = {2191},
	pages     = {179--190},
	year = {2018},
	keywords = {{Data Generation, Machine Learning, Predictive Maintenance, Industry 4.0}},
	abstract = {Today, manufacturing machines are continuously equippedwith various sensors, whose data enable to derive a comprehensive picture of the current state of each machine. Predictive maintenance approaches make use of  this data in order to predict the occurrence of possible failures before they actually occur, thereby significantly reducing production and service costs. The application of machine learning to sensor data streams is an essential part of data-driven predictive maintenance in order to find the patterns in  the data that are indicators of upcoming faults.  Thus, research on machine learning for  predictive maintenance is a recent and very challenging field. However, there are currently  no appropriate data sets available that can be used for thiskind of research. In this paper we therefore propose an approach for the generation of predictive maintenance data by using a physical Fischertechnik model factory equipped with several sensors. Different ways of reproducing real failures using this model are presented as well as a general procedure for data generation.}
}

Today, manufacturing machines are continuously equippedwith various sensors, whose data enable to derive a comprehensive picture of the current state of each machine. Predictive maintenance approaches make use of this data in order to predict the occurrence of possible failures before they actually occur, thereby significantly reducing production and service costs. The application of machine learning to sensor data streams is an essential part of data-driven predictive maintenance in order to find the patterns in the data that are indicators of upcoming faults. Thus, research on machine learning for predictive maintenance is a recent and very challenging field. However, there are currently no appropriate data sets available that can be used for thiskind of research. In this paper we therefore propose an approach for the generation of predictive maintenance data by using a physical Fischertechnik model factory equipped with several sensors. Different ways of reproducing real failures using this model are presented as well as a general procedure for data generation.

@inproceedings{malburg_workflow_reuse_2018,
	publisher = {CEUR-WS.org},
	title = {{Query Model and Similarity-Based Retrieval for Workflow Reuse in the Digital Humanities}},
	url = {http://www.wi2.uni-trier.de/publications/2018_MalburgMuensterZeyenBergmann_LWDA.pdf},
	booktitle = {Proceedings of the Conference "Lernen, Wissen, Daten, Analysen", {LWDA} 2018},
	author = {Malburg, Lukas and M{\"u}nster, Nicolas and Zeyen, Christian and Bergmann, Ralph},
	volume    = {2191},
	pages     = {251--262},
	year = {2018},
	keywords = {{Case-Based Reasoning, Workflow Reuse, Scientific Workflows, RapidMiner, Digital Humanities}},
	abstract = {Scientific Workflows do not seem to be broadly used today in the Digital Humanities to perform text and data analysis. Although they have become established in e-Science, modeling new workflows is usually a demanding task, especially for novice users. Case-Based Reasoning (CBR) has been applied in the past to support the development of workflows as an experience-based activity by retrieving past workflows. A query language is needed for this purpose, but current languages do not sufficiently consider different user groups and the information they can provide. To address this issue, we present a query model to support novice as well as experienced users. We  identify common expression elements from literature and integrate them in a prototypical CBR application named Reuse Assistant to support workflow reuse in the RapidMiner workflow tool. An experimental evaluation with non-expert users indicates the potential of the Reuse Assistant to facilitate workflow reuse and thus to simplify workflow development.}
}

Scientific Workflows do not seem to be broadly used today in the Digital Humanities to perform text and data analysis. Although they have become established in e-Science, modeling new workflows is usually a demanding task, especially for novice users. Case-Based Reasoning (CBR) has been applied in the past to support the development of workflows as an experience-based activity by retrieving past workflows. A query language is needed for this purpose, but current languages do not sufficiently consider different user groups and the information they can provide. To address this issue, we present a query model to support novice as well as experienced users. We identify common expression elements from literature and integrate them in a prototypical CBR application named Reuse Assistant to support workflow reuse in the RapidMiner workflow tool. An experimental evaluation with non-expert users indicates the potential of the Reuse Assistant to facilitate workflow reuse and thus to simplify workflow development.

@inproceedings{zeyen_conversational_2018,
  author    = {Christian Zeyen and
               Gilbert M{\"{u}}ller and
               Ralph Bergmann},
  editor    = {J{\'{e}}r{\^{o}}me Lang},
  title     = {A Conversational Approach to Process-Oriented Case-based Reasoning},
  booktitle = {Proceedings of the Twenty-Seventh International Joint Conference on
               Artificial Intelligence, {IJCAI} 2018, July 13-19, 2018, Stockholm,
               Sweden.},
  pages     = {5404--5408},
  publisher = {ijcai.org},
  year      = {2018},
  url       = {http://www.wi2.uni-trier.de/shared/publications/2018_ZeyenMuellerBergmann_IJCAI.pdf},
  doi       = {https://doi.org/10.24963/ijcai.2018/762}
}

@inproceedings{recap_lwda_2018,
	author = {Bergmann, Ralph and Schenkel, Ralf and Dumani, Lorik and Ollinger, Stefan},
	title = {{ReCAP - Information Retrieval and Case-Based Reasoning for Robust Deliberation and Synthesis of Arguments in the Political Discourse}},
	year = {2018},
	url = {http://www.wi2.uni-trier.de/shared/publications/2018_BergmannSchenkelDumaniOllinger_LWDA.pdf},
	booktitle = {Lernen. {Wissen}. {Daten}. {Analysen}. ({LWDA} 2018)},
	series = {{CEUR} {Workshop} {Proceedings}},
	note = {Accepted for publication}
}

@incollection{bergmann_similarity-based_2017,
	series = {Advances in {Intelligent} {Systems} and {Computing}},
	title = {Similarity-based {Retrieval} and {Automatic} {Adaptation} of {Semantic} {Workflows}},
	number = {626},
	booktitle = {Synergies {Between} {Knowledge} {Engineering} and {Software} {Engineering}},
	publisher = {Springer},
	author = {Bergmann, Ralph and M{\"u}ller, Gilbert},
	editor = {Nalepa, Grzegorz J. and Baumeister, Joachim},
	year = {2017},
	pages = {31--54}
}

@inproceedings{muller_complexity-aware_2017,
	series = {Lecture {Notes} in {Computer} {Science}},
	title = {Complexity-{Aware} {Generation} of {Workflows} by {Process}-{Oriented} {Case}-{Based}  {Reasoning}},
	volume = {2017},
	url = {http://www.wi2.uni-trier.de/shared/publications/2017_MuellerBergmann_KI.pdf},
	booktitle = {{KI} - 40th {German} {Conference} on {Artificial} {Intelligence}  {September} 25-29th, 2017: {Dortmund}, {Germany}},
	publisher = {Springer},
	author = {M{\"u}ller, Gilbert and Bergmann, Ralph},
	year = {2017},
	note = {The original publication is available at www.springerlink.com},
	pages = {207--221}
}

@inproceedings{bergmann_ever:_2017,
	title = {{EVER}: {Extraction} and {Processing} of {Procedural} {Experience} {Knowledge} in {Workflows}},
	url = {http://www.wi2.uni-trier.de/shared/publications/2017_BergmannMinorMuellerSchumacher_POCBR-ICCBR.pdf},
	booktitle = {3rd {Workshop} on {Process} {Oriented} {Case}-{Based} {Reasoning}},
	publisher = {CEUR Workshop Proceedings},
	author = {Bergmann, Ralph and Minor, Mirjam and M{\"u}ller, Gilbert and Schumacher, Pol},
	year = {2017}
}

@inproceedings{bergmann_cooking_2017,
	title = {Cooking made easy: {On} a novel approach to complexity-aware recipe generation},
	url = {http://www.wi2.uni-trier.de/shared/publications/2017_MuellerBergmann_CCC.pdf},
	booktitle = {Workshop of the 2017 {Computer} {Cooking} {Contest}},
	publisher = {CEUR Workshop Proceedings},
	author = {Bergmann, Ralph and M{\"u}ller, Gilbert},
	year = {2017}
}

@inproceedings{grumbach_using_2017,
	address = {Cambridge},
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {Using {Constraint} {Satisfaction} {Problem} {Solving} to {Enable} {Workflow} {Flexibility} by {Deviation}},
	booktitle = {Artificial {Intelligence} {XXXIV}},
	publisher = {Springer},
	author = {Grumbach, Lisa and Bergmann, Ralph},
	year = {2017},
	note = {Best technical paper award}
}

@inproceedings{grumbach_workflow_2017,
	series = {{CEUR} {Workshop} {Proceedings}},
	title = {Workflow {Flexibility} by {Deviation} by means of {Constraint} {Satisfaction} {Problem} {Solving}},
	url = {http://www.wi2.uni-trier.de/publications/2017_GrumbachBergmann_LWDA.pdf},
	booktitle = {Lernen. {Wissen}. {Daten}. {Analysen}. ({LWDA} 2017)},
	author = {Grumbach, Lisa and Bergmann, Ralph},
	year = {2017},
	pages = {212}
}

@inproceedings{rietzke_lwda_2017,
	series = {{CEUR} {Workshop} {Proceedings}},
	title = {Adaptive business process visualization for a data and constraint-based workflow approach},
	url = {http://www.wi2.uni-trier.de/publications/2017_RietzkeEtAl_LWDA.pdf},
	booktitle = {Lernen. {Wissen}. {Daten}. {Analysen}. ({LWDA} 2017)},
	author = {Rietzke, Eric and Bergmann, Ralph and Kuhn, Norbert},
	year = {2017},
	pages = {212}
}

@inproceedings{rietzke_bpm_2017,
	series = {Business Process Management Workshops},
	title = {Semantically-Oriented Business Process Visualization for a Data and Constraint-Based Workflow Approach},
	url = {http://www.wi2.uni-trier.de/publications/2017_RietzkeEtAl_BPAI.pdf},
	booktitle = {BPM 2017 International Workshops},
	author = {Rietzke, Eric and Bergmann, Ralph and Kuhn, Norbert},
	year = {2017},
	pages = {142-150}
}

@inproceedings{zeyen_conversational_2017,
	title = {Conversational retrieval of cooking recipes},
	url = {http://www.wi2.uni-trier.de/shared/publications/2017_ZeyenMuellerBergmann_CCC.pdf},
	booktitle = {Workshop of the 2017 {Computer} {Cooking} {Contest}},
	publisher = {CEUR Workshop Proceedings},
	author = {Zeyen, Christian and M{\"u}ller, Gilbert and Bergmann, Ralph},
	year = {2017}
}

@inproceedings{zeyen_conversational_2017-1,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {Conversational {Process}-{Oriented} {Case}-{Based} {Reasoning}},
	volume = {10339},
	url = {http://www.wi2.uni-trier.de/shared/publications/2017_ZeyenMuellerBergmann_ICCBR.pdf},
	booktitle = {Case-{Based} {Reasoning} {Research} and {Development}: 25th {International} {Conference}, {ICCBR} 2017, {Trondheim}, {Norway}, {June} 26-28, 2017, {Proceedings}},
	publisher = {Springer International Publishing},
	author = {Zeyen, Christian and M{\"u}ller, Gilbert and Bergmann, Ralph},
	editor = {Aha, David W. and Lieber, Jean},
	year = {2017},
	note = {The original publication is available at www.springerlink.com},
	pages = {403--419}
}

@techreport{bergmann_ever_2016,
	title = {{EVER} - {Extraction} and {Processing} of {Procedural} {Experience} {Knowledge} in {Workflows}},
	institution = {Universit{\"a}t Trier, Lehrstuhl f{\"u}r Wirtschaftsinformatik II},
	author = {Bergmann, Ralph and Minor, Mirjam and M{\"u}ller, Gilbert and Schumacher, Pol},
	year = {2016},
	pages = {1--9}
}

@inproceedings{grumbach_semaflex_2016,
	series = {{CEUR} {Workshop} {Proceedings}},
	title = {{SEMAFLEX} - {Semantic} {Integration} of {Flexible} {Workflow} and {Document} {Management}},
	volume = {1670},
	url = {http://www.wi2.uni-trier.de/publications/2016_GrumbachtEtAl_LWDA.pdf},
	booktitle = {Lernen. {Wissen}. {Daten}. {Analysen}. ({LWDA} 2016)},
	author = {Grumbach, Lisa and Rietzke, Eric and Schwinn, Markus and Bergmann, Ralph and Kuhn, Norbert and Krestel, Ralf and Mottin, Davide and M{\"u}ller, Emmanuel},
	year = {2016},
	pages = {43--50}
}

@inproceedings{pfister_ahnlichkeitsbasiertes_2016,
	series = {{CEUR} {Workshop} {Proceedings}},
	title = {{\"A}hnlichkeitsbasiertes {Retrieval} von {BPMN}-2.0-{Modellen}},
	volume = {1670},
	url = {http://www.wi2.uni-trier.de/publications/2016_PfisterFuchsBergmann_LWDA.pdf},
	booktitle = {Lernen. {Wissen}. {Daten}. {Analysen}. ({LWDA} 2016)},
	author = {Pfister, Maximilian and Fuchs, Florian and Bergmann, Ralph},
	editor = {Krestel, Ralf and Mottin, Davide and M{\"u}ller, Emmanuel},
	year = {2016},
	pages = {54--61}
}

@inproceedings{bergmann_retrieving_2016,
	address = {Key Largo, Florida, USA},
	title = {Retrieving {Adaptable} {Cases} in {Process}-{Oriented} {Case}-{Based} {Reasoning}},
	url = {http://www.wi2.uni-trier.de/publications/2016_Bergmann_Flairs.pdf},
	abstract = {This paper presents a novel approach to retrieval in
process-oriented case-based reasoning (POCBR) which
considers the adaptability of workflows cases during
the retrieval phase. A novel concept of adaptability in
POCBR is proposed, which assesses the potential similarity
increase of a case which can be gained by adaptation.
The adaptability of a case is learned from the case
base in an off-line pre-processing phase prior to the retrieval.
The proposed approach is generic as it can be
used in combination with different adaptation methods.
An empirical evaluation in the domain of cooking workflows
demonstrates the benefit of the approach.},
	booktitle = {Proceedings of the {Twenty}-{Ninth} {International} {Florida} {Artificial} {Intelligence} {Research} {Society} {Conference}},
	publisher = {AAAI Press},
	author = {Bergmann, Ralph and M{\"u}ller, Gilbert and Zeyen, Christian and Manderscheid, Jens},
	editor = {Markov, Zdravko and Russel, Ingrid},
	year = {2016},
	pages = {419--424}
}

This paper presents a novel approach to retrieval in process-oriented case-based reasoning (POCBR) which considers the adaptability of workflows cases during the retrieval phase. A novel concept of adaptability in POCBR is proposed, which assesses the potential similarity increase of a case which can be gained by adaptation. The adaptability of a case is learned from the case base in an off-line pre-processing phase prior to the retrieval. The proposed approach is generic as it can be used in combination with different adaptation methods. An empirical evaluation in the domain of cooking workflows demonstrates the benefit of the approach.

@inproceedings{minor_transferability_2016,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {On the {Transferability} of {Process}-oriented {Cases}},
	volume = {9969},
	url = {http://www.wi2.uni-trier.de/publications/2016_MinorBergmann_ICCBR.pdf},
	abstract = {The paper studies the feasibility of using transfer learning
for process-oriented case-based reasoning. The work introduces a novel
approach to transfer work
ow cases from a loosely related source domain
to a target domain. The idea is to develop a representation mapper based
on work
ow generalization, work
ow abstraction, and structural analogy
in vocabulary. The approach is illustrated by a pair of sample domains on
two sub-?elds of customer relationship management, which have similar
process objectives but di?erent tasks and data to ful?ll them. An experiment
with expert ratings of transferred cases is conducted to test the
feasibility of the approach with promising results for work
ow modelling
support.},
	booktitle = {Case-{Based} {Reasoning} {Research} and {Development} - 24nd {International} {Conference}, {ICCBR} 2016, {Atlanta}, {USA}. {Proceedings}},
	publisher = {Springer},
	author = {Minor, Mirjam and Bergmann, Ralph and M{\"u}ller, Jan-Martin and Sp{\"a}t, Alexander},
	editor = {Goel, Ashok K. and Diaz-Agudo, Belen and Roth-Berghofer, Thomas},
	year = {2016},
	note = {The original publication is available at www.springerlink.com},
	pages = {281--294}
}

The paper studies the feasibility of using transfer learning for process-oriented case-based reasoning. The work introduces a novel approach to transfer work ow cases from a loosely related source domain to a target domain. The idea is to develop a representation mapper based on work ow generalization, work ow abstraction, and structural analogy in vocabulary. The approach is illustrated by a pair of sample domains on two sub-?elds of customer relationship management, which have similar process objectives but di?erent tasks and data to ful?ll them. An experiment with expert ratings of transferred cases is conducted to test the feasibility of the approach with promising results for work ow modelling support.

@inproceedings{muller_case_2016,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {Case {Completion} of {Workflows} for {Process}-{Oriented} {Case}-{Based} {Reasoning}},
	volume = {9969},
	url = {http://www.wi2.uni-trier.de/publications/2016_MuellerBergmann_ICCBR.pdf},
	abstract = {Cases available in real world domains are often incomplete and sometimes
lack important information. Using incomplete cases in a CBR system can
be harmful, as the lack of information can result in inappropriate similarity computations
or incompletely generated adaptation knowledge. Case completion aims
to overcome this issue by inferring missing information. This paper presents
a novel approach to case completion for process-oriented case-based reasoning
(POCBR). In particular, we address the completion of workflow cases by
adding missing or incomplete dataflow information. Therefore, we combine automatically
learned domain specific completion operators with generic domainindependent
default rules. The empirical evaluation demonstrates that the presented
completion approach is capable of deriving complete workflows with high
quality and a high degree of completeness.},
	booktitle = {Case-{Based} {Reasoning} {Research} and {Development} - 24nd {International} {Conference}, {ICCBR} 2016, {Atlanta}, {USA}. {Proceedings}},
	publisher = {Springer},
	author = {M{\"u}ller, Gilbert and Bergmann, Ralph},
	editor = {Goel, A. and Diaz-Agudo, B. and Roth-Berghofer, Thomas},
	year = {2016},
	note = {The original publication is available at www.springerlink.com},
	pages = {295--310}
}

Cases available in real world domains are often incomplete and sometimes lack important information. Using incomplete cases in a CBR system can be harmful, as the lack of information can result in inappropriate similarity computations or incompletely generated adaptation knowledge. Case completion aims to overcome this issue by inferring missing information. This paper presents a novel approach to case completion for process-oriented case-based reasoning (POCBR). In particular, we address the completion of workflow cases by adding missing or incomplete dataflow information. Therefore, we combine automatically learned domain specific completion operators with generic domainindependent default rules. The empirical evaluation demonstrates that the presented completion approach is capable of deriving complete workflows with high quality and a high degree of completeness.

@inproceedings{muller_cookingcake:_2015,
	address = {Springer},
	title = {{CookingCAKE}: {A} {Framework} for the adaptation of cooking recipes represented as workflows},
	url = {http://www.wi2.uni-trier.de/publications/2015_MuellerBergmannCCC.pdf},
	booktitle = {Computer {Cooking} {Contest}, {Workshop} {Proceedings} {ICCBR} 2015},
	author = {M{\"u}ller, Gilbert and Bergmann, Ralph},
	year = {2015}
}

@article{gorg_social_2015,
	series = {Elsevier},
	title = {Social workflows - {Vision} and potential study},
	volume = {50},
	issn = {0306-4379},
	url = {http://www.wi2.uni-trier.de/publications/2015_GoergBergmannIS.pdf},
	doi = {http://dx.doi.org/10.1016/j.is.2014.12.007},
	number = {0},
	journal = {Information Systems},
	author = {G{\"o}rg, Sebastian and Bergmann, Ralph},
	year = {2015},
	note = {Only preprint of this article available for download},
	pages = {1--19}
}

@inproceedings{gessinger_flexible_2015,
	address = {Trier},
	series = {{CEUR} {Workshop} {Proceedings}},
	title = {Flexible {Process}-{Aware} {Information} {Systems} for {Deficiency} {Management} in {Construction}},
	volume = {1458},
	url = {http://www.wi2.uni-trier.de/publications/2015_GessingerBergmannLWA.pdf},
	booktitle = {Proceedings of the {LWA} 2015 {Workshops}: {KDML}, {FGWM}, {IR}, and {FGDB}},
	author = {Gessinger, Sarah and Bergmann, Ralph},
	editor = {Bergmann, Ralph and G{\"o}rg, Sebastian and M{\"u}ller, Gilbert},
	year = {2015},
	pages = {330--338}
}

@inproceedings{muller_poql:_2015,
	address = {Trier},
	series = {{CEUR} {Workshop} {Proceedings}},
	title = {{POQL}: {A} {New} {Query} {Language} for {Process}-{Oriented} {Case}-{Based} {Reasoning}},
	volume = {1458},
	url = {http://www.wi2.uni-trier.de/publications/2015_MuellerBergmannLWA.pdf},
	booktitle = {Proceedings of the {LWA} 2015 {Workshops}: {KDML}, {FGWM}, {IR}, and {FGDB}},
	author = {M{\"u}ller, Gilbert and Bergmann, Ralph},
	editor = {Bergmann, Ralph and G{\"o}rg, Sebastian and M{\"u}ller, Gilbert},
	year = {2015},
	pages = {247--255}
}

@inproceedings{muller_generalization_2015,
	address = {Hollywood (Florida), USA},
	title = {Generalization of {Workflows} in {Process}-{Oriented} {Case}-{Based} {Reasoning}},
	url = {http://www.wi2.uni-trier.de/publications/2015_MuellerBergmannFLAIRS.pdf},
	booktitle = {28th {International} {FLAIRS} {Conference}},
	publisher = {AAAI Press},
	author = {M{\"u}ller, Gilbert and Bergmann, Ralph and Russel, Ingrid and Eberle, William},
	year = {2015},
	pages = {391--396}
}

@inproceedings{muller_learning_2015,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {Learning and {Applying} {Adaptation} {Operators} in {Process}-{Oriented} {Case}-{Based} {Reasoning}},
	volume = {9343},
	url = {http://www.wi2.uni-trier.de/publications/2015_MuellerBergmannICCBR.pdf},
	booktitle = {Case-{Based} {Reasoning} {Research} and {Development} - 23nd {International} {Conference}, {ICCBR} 2015, {Frankfurt}, {Germany}, {September} 28, 2015 - {September} 30, 2015. {Proceedings}},
	publisher = {Spinger},
	author = {M{\"u}ller, Gilbert and Bergmann, Ralph},
	editor = {H{\"u}llermeier, Eyke and Minor, Mirjam},
	year = {2015},
	pages = {259--274}
}

@inproceedings{muller_compositional_2014,
	address = {Springer},
	title = {Compositional {Adaptation} of {Cooking} {Recipes} using {Workflow} {Streams}},
	url = {http://www.wi2.uni-trier.de/publications/2014_MuellerBergmannCCC.pdf},
	booktitle = {Computer {Cooking} {Contest}, {Workshop} {Proceedings} {ICCBR} 2014},
	author = {M{\"u}ller, Gilbert and Bergmann, Ralph},
	year = {2014},
	note = {The original publication is available at www.springerlink.com}
}

@article{minor_case-based_2014,
	series = {Elsevier},
	title = {Case-based adaptation of workflows},
	volume = {40},
	url = {http://www.sciencedirect.com/science/article/pii/S0306437912001536},
	doi = {10.1016/j.is.2012.11.011},
	journal = {Information Systems},
	author = {Minor, Mirjam and Bergmann, Ralph and G{\"o}rg, Sebastian},
	year = {2014},
	pages = {142--152}
}

@article{bergmann_similarity_2014,
	series = {Elsevier},
	title = {Similarity {Assessment} and {Efficient} {Retrieval} of {Semantic} {Workfows}},
	volume = {40},
	url = {http://www.wi2.uni-trier.de/publications/2012_BergmannGilISJ.pdf},
	doi = {10.1016/j.is.2012.07.005},
	journal = {Information Systems},
	author = {Bergmann, Ralph and Gil, Yolanda},
	year = {2014},
	note = {Only preprint of this article available for download},
	pages = {115--127}
}

@inproceedings{bergmann_collaborative_2014,
	address = {New York, NY, USA},
	series = {{GROUP} '14},
	title = {The {Collaborative} {Agile} {Knowledge} {Engine} {CAKE}},
	isbn = {978-1-4503-3043-5},
	url = {http://www.wi2.uni-trier.de/publications/2014_CAKE_ACM.pdf},
	doi = {10.1145/2660398.2663771},
	abstract = {The Collaborative Agile Knowledge Engine (CAKE) is a prototypical generic software system for integrated process and knowledge management. CAKE integrates recent research results on agile workflows, process-oriented case-based reasoning, and web technologies into a common platform that can be configured to different application domains and needs. We describe the main concepts and the architecture of CAKE and sketch three example applications.},
	urldate = {2014-12-11},
	booktitle = {Proceedings of the 18th {International} {Conference} on {Supporting} {Group} {Work}},
	publisher = {ACM},
	author = {Bergmann, Ralph and Gessinger, Sarah and G{\"o}rg, Sebastian and M{\"u}ller, Gilbert},
	year = {2014},
	keywords = {agile workflows, case-based reasoning, knowledge management, process management},
	pages = {281--284}
}

The Collaborative Agile Knowledge Engine (CAKE) is a prototypical generic software system for integrated process and knowledge management. CAKE integrates recent research results on agile workflows, process-oriented case-based reasoning, and web technologies into a common platform that can be configured to different application domains and needs. We describe the main concepts and the architecture of CAKE and sketch three example applications.

@article{bonjour_enhancing_2014,
	title = {Enhancing experience reuse and learning},
	volume = {68},
	issn = {0950-7051},
	url = {http://www.sciencedirect.com/science/article/pii/S0950705114002457},
	doi = {http://doi.org/10.1016/j.knosys.2014.06.024},
	journal = {Knowledge-Based Systems},
	author = {Bonjour, Eric and Geneste, Laurent and Bergmann, Ralph},
	year = {2014},
	pages = {1 -- 3}
}

@techreport{bergmann_weda_2014,
	title = {{WEDA} {\textendash} {Web}-basierte {Erstellung}, {Wiederverwendung}, {Dokumentation} und {Ablaufunterst{\"u}tzung} agiler {Workflows}. {Abschussbericht}.},
	institution = {Universit{\"a}t Trier, Lehrstuhl f{\"u}r Wirtschaftsinformatik II},
	author = {Bergmann, Ralph and G{\"o}rg, Sebastian},
	year = {2014}
}

@inproceedings{dieterle_hybrid_2014,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {A {Hybrid} {CBR}-{ANN} {Approach} to the {Appraisal} of {Internet} {Domain} {Names}},
	url = {http://www.wi2.uni-trier.de/publications/2014_DieterleBergmannICCBR.pdf},
	booktitle = {Case-{Based} {Reasoning} {Research} and {Development}, 22th {International} {Conference} on {Case}-{Based} {Reasoning}, {ICCBR} 2014},
	publisher = {Springer},
	author = {Dieterle, Sebastian and Bergmann, Ralph},
	editor = {Lamontagne, Luc and Plaza, Enric},
	year = {2014},
	note = {The original publication is available at www.springerlink.com},
	pages = {95--109}
}

@inproceedings{muller_cluster-based_2014,
	address = {IOS Press},
	title = {A {Cluster}-{Based} {Approach} to {Improve} {Similarity}-{Based} {Retrieval} for {Process}-{Oriented} {Case}-{Based} {Reasoning}},
	url = {http://www.wi2.uni-trier.de/publications/2014_MuellerBergmannECAI.pdf},
	booktitle = {20th {European} {Conference} on {Artificial} {Intelligence} ({ECAI} 2014)},
	author = {M{\"u}ller, Gilbert and Bergmann, Ralph},
	editor = {Schaub, Torsten and Friedrich, Gerhard and O'Sullivan, Barry},
	year = {2014},
	note = {Preprint of this article available for download.},
	pages = {639--644}
}

@inproceedings{muller_workflow_2014,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {Workflow {Streams}: {A} {Means} for {Compositional} {Adaptation} in {Process}-{Oriented} {CBR}},
	volume = {8765},
	url = {http://www.wi2.uni-trier.de/publications/2014_MuellerBergmannICCBR.pdf},
	booktitle = {Case-{Based} {Reasoning} {Research} and {Development} - 22nd {International} {Conference}, {ICCBR} 2014, {Cork}, {Ireland}, {September} 29, 2014 - {October} 1, 2014. {Proceedings}},
	publisher = {Springer},
	author = {M{\"u}ller, Gilbert and Bergmann, Ralph},
	editor = {Lamontagne, Luc and Plaza, Enric},
	year = {2014},
	note = {Best phd student paper award. The original publication is available at www.springerlink.com},
	pages = {315--329}
}

@inproceedings{gorg_realtime_2013,
	title = {Real-{Time} {Collaboration} and {Experience} {Reuse} {For} {Cloud} - {Based} {Workflow} {Management} {Systems}},
	url = {http://www.wi2.uni-trier.de/publications/2013_SBM_Workshop_GoergEtAl.pdf},
	booktitle = {Workshop on {Social} {Business} {Process} {Management} ({SBM} 2013)},
	publisher = {IEEE Computer Society Press},
	author = {G{\"o}rg, Sebastian and Bergmann, Ralph and Gessinger, Sarah and Minor, Mirjam},
	year = {2013}
}

@inproceedings{gessinger_potentialanalyse_2013,
	title = {Potentialanalyse des prozessorientierten {Wissensmanagement} f{\"u}r die {Baubranche}},
	url = {http://www.wi2.uni-trier.de/publications/2013_LWA_Gessinger.pdf},
	booktitle = {{LWA} 2013 {Lernen} - {Wissen} - {Adaption}},
	publisher = {Otto-Friedrich-Universit{\"a}t Bamberg},
	author = {Gessinger, Sarah and Bergmann, Ralph},
	editor = {Sperker, Hans-Christian and Henrich, Andreas and Schmid, Ute},
	year = {2013},
	pages = {212--219}
}

@inproceedings{bergmann_workflow_2013,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {Workflow {Clustering} {Using} {Semantic} {Similarity} {Measures}},
	volume = {8077},
	url = {http://www.wi2.uni-trier.de/publications/2013_BergmannMuellerWittkowskyKI.pdf},
	booktitle = {{KI} 2013: {Advances} in {Artificial} {Intelligence}},
	publisher = {Springer},
	author = {Bergmann, Ralph and M{\"u}ller, Gilbert and Wittkowsky, Daniel},
	editor = {Timm, Ingo and Thimm, Matthias},
	year = {2013},
	note = {The original publication is available at www.springerlink.com}
}

@inproceedings{bergmann_mac/fac_2013,
	title = {{MAC}/{FAC} {Retrieval} of {Semantic} {Workflows}},
	url = {http://www.wi2.uni-trier.de/publications/2013_FLAIRS_BergmannStromer.pdf},
	booktitle = {Proceedings of the {Twenty}-{Sixth} {International} {Florida} {Artificial} {Intelligence} {Research} {Society} {Conference}, {St}. {Pete} {Beach}, {May} 22-25, 2013.},
	publisher = {AAAI Press},
	author = {Bergmann, Ralph and Stromer, Alexander},
	editor = {Boonthum-Denecke, C. and Youngblood, G. Michael},
	year = {2013},
	pages = {357 -- 362}
}

@inproceedings{gorg_resource_2013,
	title = {A {Resource} {Model} for {Cloud}-{Based} {Workflow} {Management} {Systems} - {Enabling} {Access} {Control}, {Collaboration} and {Reuse}},
	url = {http://www.wi2.uni-trier.de/publications/2013_CLOSER-GoergEtAl.pdf},
	booktitle = {Proceedings of the 3rd {International} {Conference} on {Cloud} {Computing} and {Services} {Science}, {Aachen}, {Germany}, 2013},
	publisher = {SciTePress 2013},
	author = {G{\"o}rg, Sebastian and Bergmann, Ralph and Gessinger, Sarah and Minor, Mirjam},
	year = {2013},
	pages = {263--272}
}

@inproceedings{bergmann_ralph_scaling_2012,
	address = {Lyon},
	title = {Scaling similarity-based retrieval of semantic workflows},
	url = {http://www.wi2.uni-trier.de/publications/2012_ICCBR_POCBR_Bergmann_etal.pdf},
	booktitle = {{ICCBR}-{Workshop} on {Process}-oriented {Case}-{Based} {Reasoning}},
	author = {{Bergmann, Ralph} and {Minor, Mirjam} and {Islam, Siblee} and {Schumacher, Pol} and {Stromer, Alexander}},
	editor = {{Lamontagne, Luc} and {Recio-Garcia, Juan A.}},
	year = {2012},
	pages = {15--24}
}

@inproceedings{gorg_collecting_2012,
	title = {Collecting, reusing and executing private workflows on social network platforms},
	isbn = {978-1-4503-1230-1},
	url = {http://www.wi2.uni-trier.de/publications/2012_WWW_GoergEtal.pdf},
	booktitle = {Proceedings of the 21st {World} {Wide} {Web} {Conference}, {WWW} 2012, {Lyon}, {France}, {April} 16-20, 2012 ({Companion} {Volume})},
	publisher = {ACM},
	author = {G{\"o}rg, Sebastian and Bergmann, Ralph and Minor, Mirjam and Gessinger, Sarah and Islam, Siblee},
	editor = {Mille, Alain and Gandon, Fabien L. and Misselis, Jacques and Rabinovich, Michael and Staab, Steffen},
	year = {2012},
	pages = {747--750}
}

@inproceedings{schumacher_extraction_2012,
	address = {Lyon, France},
	title = {Extraction of {Procedural} {Knowledge} from the {Web}},
	url = {http://www.wi2.uni-trier.de/publications/2012_WWW_SchumacherEtal.pdf},
	booktitle = {Proceedings of the 21st {World} {Wide} {Web} {Conference}, {WWW} 2012, {Lyon}, {France}, {April} 16-20, 2012 ({Companion} {Volume})},
	publisher = {ACM},
	author = {Schumacher, Pol and Minor, Mirjam and Walter, Kirstin and Bergmann, Ralph},
	editor = {Mille, Alain and Gandon, Fabien L. and Misselis, Jacques and Rabinovich, Michael and Staab, Steffen},
	year = {2012},
	file = {wk2fp3-schumacher.pdf:C\:\\Users\\Zeyen\\Zotero\\storage\\HKDMQUMQ\\wk2fp3-schumacher.pdf:application/pdf}
}

@inproceedings{dieterle_case-based_2012,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {Case-{Based} {Appraisal} of {Internet} {Domains}},
	volume = {7466},
	url = {http://www.wi2.uni-trier.de/publications/2012_ICCBR_Dieterle_Bergmann_springer.pdf},
	booktitle = {Case-{Based} {Reasoning}. {Research} and {Development}, 20th {International} {Conference} on {Case}-{Based} {Reasoning}, {ICCBR} 2012},
	publisher = {Springer},
	author = {Dieterle, Sebastian and Bergmann, Ralph},
	editor = {Watson, Ian},
	collaborator = {Diaz-Agudo, Belen},
	year = {2012},
	note = {The original publication is available at www.springerlink.com},
	keywords = {CBR, Application},
	pages = {47--61}
}

@inproceedings{walter_workflow_2011,
	title = {Workflow {Extraction} from {Cooking} {Recipes}},
	url = {http://www.wi2.uni-trier.de/publications/2011_CCC_WalterEtal.pdf},
	booktitle = {Proceedings of the {ICCBR} 2011 {Workshops}},
	author = {Walter, Kirstin and Minor, Mirjam and Bergmann, Ralph},
	editor = {Diaz-Agudo, Belen and Cordier, Amelie},
	year = {2011},
	pages = {207--216}
}

@inproceedings{minor_adaptive_2011,
	title = {Adaptive {Workflow} {Management} in the {Cloud} -{Towards} a {Novel} {Platform} as a {Service}},
	url = {http://www.wi2.uni-trier.de/publications/2011_POCBR_MinorEtal.pdf},
	booktitle = {Proceedings of the {ICCBR} 2011 {Workshops}},
	author = {Minor, Mirjam and Bergmann, Ralph and G{\"o}rg, Sebastian},
	year = {2011},
	pages = {131--138}
}

@inproceedings{bergmann_retrieval_2011,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {Retrieval of {Semantic} {Workfows} with {Knowledge} {Intensive} {Similarity} {Measures}},
	volume = {6880},
	url = {http://www.wi2.uni-trier.de/publications/2011_BergmannGilICCBR2011CRC.pdf},
	booktitle = {Case-{Based} {Reasoning}. {Research} and {Development}, 19th {International} {Conference} on {Case}-{Based} {Reasoning}, {ICCBR} 2011},
	publisher = {Springer},
	author = {Bergmann, Ralph and Gil, Yolanda and Ram, Ashwin and Wiratunga, N.},
	year = {2011},
	note = {The original publication is available at www.springerlink.com},
	pages = {17--31}
}

@inproceedings{minor_reasoning_2011,
	title = {Reasoning on {Business} {Processes} to {Support} {Change} {Reuse}},
	isbn = {978-1-4577-1542-6},
	url = {http://www.wi2.uni-trier.de/publications/2011_CEC11_Minor_etal},
	booktitle = {13th {IEEE} {Conference} on {Commerce} and {Enterprise} {Computing}, {CEC} 2011, {Luxembourg}-{Kirchberg}, {Luxembourg}, {September} 5-7, 2011},
	publisher = {IEEE Computer Society},
	author = {Minor, Mirjam and Bergmann, Ralph and G{\"o}rg, Sebastian and Walter, Kirstin},
	editor = {Hofreiter, Birgit and Dubois, Eric and Lin, Kwei-Jay and Setzer, Thomas and Godart, Claude and Proper, Erik and Bodenstaff, Lianne},
	year = {2011},
	pages = {18--25},
	file = {submissionMinorCEC11.pdf:C\:\\Users\\Zeyen\\Zotero\\storage\\QZGFDTW8\\submissionMinorCEC11.pdf:application/pdf}
}

@inproceedings{sauer_inverse_2011,
	series = {{LNI}},
	title = {Inverse {Workflows} for {Supporting} {Agile} {Business} {Process} {Management}},
	volume = {182},
	url = {http://www.wi2.uni-trier.de/publications/2011_WM_SauerEtAl.pdf},
	booktitle = {{WM} 2011: 6th {Conference} on {Professional} {Knowledge} {Management}},
	publisher = {Gesellschaft f{\"u}r Informatik (GI)},
	author = {Sauer, Thomas and Minor, Mirjam and Bergmann, Ralph},
	editor = {Maier, Ronald},
	year = {2011},
	pages = {204--213}
}

@incollection{minor_agile_2010,
	title = {Agile {Workflow} {Technology} for {Long}-{Term} {Processes} - {Enhanced} by {Case}-{Based} {Change} {Reuse}},
	url = {http://www.igi-global.com/bookstore/titledetails.aspx?titleid=37223},
	booktitle = {Methodological {Advancements} in {Intelligent} {Information} {Technologies}: {Evolutionary} {Trends}},
	publisher = {IGI Global},
	author = {Minor, Mirjam and Tartakovski, Alexander and Schmalen, Daniel and Bergmann, Ralph},
	year = {2010},
	pages = {279--298}
}

@inproceedings{minor_adaptation_2010,
	title = {Adaptation of {Cooking} {Instructions} {Following} the {Workflow} {Paradigm}},
	url = {http://www.wi2.uni-trier.de/publications/2010_CCC.pdf},
	booktitle = {{ICCBR} 2010 {Workshop} {Proceedings}},
	author = {Minor, Mirjam and Bergmann, Ralph and G{\"o}rg, Sebastian and Walter, Kirstin},
	editor = {Marling, Cindy},
	year = {2010},
	pages = {199--208}
}

@inproceedings{minor_towards_2010,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {Towards {Case}-{Based} {Adaptation} of {Workflows}},
	volume = {6176},
	url = {http://www.wi2.uni-trier.de/publications/2010_MinorEtalICCBR.pdf},
	booktitle = {Case-{Based} {Reasoning}. {Research} and {Development}, 18th {International} {Conference} on {Case}-{Based} {Reasoning}, {ICCBR} 2010, {Alessandria},{Italy}, {July} 19-22, 2010.},
	publisher = {Springer},
	author = {Minor, Mirjam and Bergmann, Ralph and G{\"o}rg, Sebastian and Walter, Kirstin},
	editor = {Montani, Stefania and Bichindaritz, Isabelle},
	year = {2010},
	note = {The original publication is available at www.springerlink.com},
	pages = {421--435}
}

@article{bergmann_case-based_2009,
	title = {Case-{Based} {Reasoning} - {Introduction} and {Recent} {Developments}},
	volume = {1/2009},
	url = {http://www.wi2.uni-trier.de/publications/2009_KI_CBR.pdf},
	journal = {K{\"u}nstliche Intelligenz},
	author = {Bergmann, Ralph and Althoff, Klaus-Dieter and Minor, Mirjam and Reichle, Meike and Bach, Kerstin},
	year = {2009},
	pages = {5--11}
}

@inproceedings{fuchs_cooking_2009,
	title = {Cooking {Cake}},
	url = {http://www.wi2.uni-trier.de/publications/2009_CookingCake.pdf},
	booktitle = {Computer {Cooking} {Contest}, {Workshop} {Proceedings} {ICCBR} 2010},
	author = {Fuchs, Christian and Gimmler, Christoph and G{\"u}nther, Simon and Holthof, Lukas and Bergmann, Ralph},
	editor = {Minor, Mirjam and Stahl, Armin and Leake, David},
	year = {2009},
	pages = {259 -- 268}
}

@inproceedings{bergmann_improving_2009,
	title = {Improving {KD}-{Tree} {Based} {Retrieval} for {Attribute} {Dependent} {Generalized} {Cases}},
	isbn = {978-1-57735-419-2},
	url = {http://www.wi2.uni-trier.de/publications/2009_flairs.pdf},
	booktitle = {Proceedings of the {Twenty}-{Second} {International} {Florida} {Artificial} {Intelligence} {Research} {Society} {Conference}, {May} 19-21, 2009, {Sanibel} {Island}, {Florida}, {USA}},
	publisher = {AAAI Press},
	author = {Bergmann, Ralph and Tartakovski, Alexander},
	editor = {Lane, H. Chad and Guesgen, Hans W.},
	year = {2009}
}

@article{minor_agile_2008,
	title = {Agile {Workflow} {Technology} and {Case}-{Based} {Change} {Reuse} for {Long}-{Term} {Processes}},
	volume = {4},
	url = {http://www.igi-global.com/bookstore/titledetails.aspx?titleid=34478&detailstype=contents},
	number = {1},
	journal = {International Journal of Intelligent Information Technologies},
	author = {Minor, Mirjam and Tartakovski, Alexander and Schmalen, Daniel and Bergmann, Ralph},
	year = {2008},
	pages = {80--98}
}

@inproceedings{minor_xml-based_2008,
	title = {{XML}-based {Representation} of {Agile} {Workflows}},
	url = {http://www.wi2.uni-trier.de/publications/2008_MKWI_MinorEtal.pdf},
	booktitle = {Multikonferenz {Wirtschaftsinformatik} 2008},
	publisher = {GITO-Verlag Berlin},
	author = {Minor, Mirjam and Schmalen, Daniel and Bergmann, Ralph},
	editor = {Bichler, Martin and Hess, Thomas and Krcmar, Helmut and Lechner, Ulrike and Matthes, Florian and Picot, Arnold and Speitkamp, Benjamin and Wolf, Petra},
	year = {2008},
	pages = {439--440}
}

@inproceedings{fresmann_mobile_2007,
	title = {Mobile {Knowledge} {Management} {Support} in {Fire} {Service} {Organisations}},
	volume = {2},
	url = {http://www.wi2.uni-trier.de/publications/2007_WI_amira.pdf},
	booktitle = {Tagungsband der 8. {Internationalen} {Tagung} der {Wirtschaftsinformatik}},
	publisher = {Universit{\"a}tsverlag Karlsruhe},
	author = {Fre{\ss}mann, Andrea and Bergmann, Ralph and Taylor, Brian and Diamond, Ben and Carr-Smith, Gary},
	editor = {Oberweis and Weinhardt and Gimpel and Koschmider and Pankratius and Schnizler},
	year = {2007},
	pages = {557--574}
}

@inproceedings{bergmann_ambient_2007,
	series = {Lecture {Notes} in {Computer} {Science}},
	title = {Ambient {Intelligence} for {Decision} {Making} in {Fire} {Service} {Organizations}},
	volume = {4794},
	isbn = {978-3-540-76651-3},
	url = {http://www.wi2.uni-trier.de/publications/2007_AMI.pdf},
	booktitle = {Ambient {Intelligence}, {European} {Conference}, {AmI} 2007, {Darmstadt}, {Germany}, {November} 7-10, 2007, {Proceedings}},
	publisher = {Springer},
	author = {Bergmann, Ralph},
	editor = {Schiele, Bernt and Dey, Anind K. and Gellersen, Hans and Ruyter, Boris E. R. de and Tscheligi, Manfred and Wichert, Reiner and Aarts, Emile H. L. and Buchmann, Alejandro P.},
	year = {2007},
	note = {The original publication is available at www.springerlink.com},
	pages = {73--90}
}

@inproceedings{minor_structural_2007,
	title = {Structural adaptation of workflows supported by a suspension mechanism and by case-based reasoning},
	url = {http://www.wi2.uni-trier.de/publications/2007_WETICE_MinorEtal.pdf},
	booktitle = {Proceedings of the 16th {IEEE} {International} {Workshop} on {Enabling} {Technologies}: {Infrastructure} for {Collaborative} {Enterprises} ({WETICE}'07), {June} 18 - 20, 2007, {Paris}, {France}},
	publisher = {IEEE Computer Society, Los Alamitos, California},
	author = {Minor, Mirjam and Schmalen, Daniel and Koldehoff, Andreas and Bergmann, Ralph},
	editor = {Reddy, Sumitra Mitra},
	year = {2007},
	note = {Best Paper},
	pages = {370--375}
}

@inproceedings{giese_using_2007,
	title = {Using {Ontology}-{Mapping} {Techniques} for {Content}-based {Result} {Merging}},
	volume = {2},
	url = {http://www.wi2.uni-trier.de/publications/2007_wm07_EM.pdf},
	booktitle = {4th {Conference} on {Professional} {Knowledge} {Management} - {Experience} and {Visions}},
	publisher = {GITO-Verlag Berlin},
	author = {Giese, Michael and Fre{\ss}mann, Andrea and Bergmann, Ralph},
	editor = {Gronau, Norbert},
	year = {2007},
	pages = {127--134}
}

@inproceedings{minor_configurable_2007,
	title = {Configurable {Contexts} for {Experience} {Management}},
	volume = {2},
	url = {http://www.wi2.uni-trier.de/publications/2007_WM_MinorEtal.pdf},
	booktitle = {4th {Conference} on {Professional} {Knowledge} {Management} - {Experiences} and {Visions}},
	publisher = {GITO-Verlag Berlin},
	author = {Minor, Mirjam and Koldehoff, Andreas and Schmalen, Daniel and Bergmann, Ralph},
	editor = {Gronau, Norbert},
	month = mar,
	year = {2007},
	pages = {119--126}
}

@inproceedings{minor_representation_2007,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {Representation and {Structure}-based {Similarity} {Assessment} for {Agile} {Workflows}},
	volume = {4626},
	url = {http://www.wi2.uni-trier.de/publications/2007_ICCBR_MinorEtal.pdf},
	booktitle = {Case-{Based} {Reasoning} {Research} and {Development}, 7th {International} {Conference} on {Case}-{Based} {Reasoning}, {ICCBR} 2007, {Belfast}, {Northern} {Ireland}, {UK}, {August} 2007, {Proceedings}},
	publisher = {Springer},
	author = {Minor, Mirjam and Tartakovski, Alexander and Bergmann, Ralph},
	editor = {Weber, Rosina O and Richter, Michael M},
	year = {2007},
	note = {The original publication is available at www.springerlink.com},
	pages = {224--238}
}

@article{nick_experience_2007,
	title = {Experience {Management}},
	volume = {21},
	url = {http://www.wi2.uni-trier.de/publications/2007_Experience Management Schlagwort.pdf},
	number = {2},
	journal = {KI - K{\"u}nstliche Intelligenz},
	author = {Nick, Markus and Althoff, Klaus-Dieter and Bergmann, Ralph},
	year = {2007},
	pages = {50--52}
}

@inproceedings{minor_flexible_2006,
	title = {Flexible {Workflows} for {Knowledge} {Management} in the {Digital} {Design}},
	url = {http://www.wi2.uni-trier.de/publications/2006_FGWM_MinorEtal.pdf},
	booktitle = {{LWA} 2006 {Lernen} - {Wissensentdeckung} - {Adaptivit{\"a}t}, 9.-11.10.2006 in {Hildesheim}},
	author = {Minor, Mirjam and Koldehoff, Andreas and Schmalen, Daniel and Bergmann, Ralph},
	editor = {Schaaf, Martin and Althoff, Klaus-Dieter},
	year = {2006},
	pages = {215 -- 219}
}

@inproceedings{muller_knowledge_2006,
	address = {Hildesheim},
	title = {Knowledge {Search} within a {Company}-{WIKI}},
	url = {http://www.wi2.uni-trier.de/publications/2006_LWA_paper_final.pdf},
	booktitle = {{LWA} 2006 : {Lernen} - {Wissensentdeckung} - {Adaptivit{\"a}t}},
	author = {M{\"u}ller, Stephanie and Kritzler, Nils and Tartakovski, Alexander and Bergmann, Ralph and Traph{\"o}ner, Ralph},
	editor = {Schaaf, Martin and Althoff, Klaus-Dieter},
	year = {2006},
	pages = {209--214}
}

@inproceedings{sauer_supporting_2006,
	address = {Passau, Germany},
	title = {Supporting {Collaborative} {Business} through {Integration} of {Knowledge} {Distribution} and {Agile} {Process} {Management}},
	url = {http://www.wi2.uni-trier.de/publications/2006_MKWI_sauer.pdf},
	booktitle = {Multikonferenz {Wirtschaftsinformatik} 2006 ({MKWI} 2006), {Teilkonferenz} "{Collaborative} {Business}"},
	publisher = {GITO-Verlag Berlin},
	author = {Sauer, Thomas and Maximini, Kerstin and Maximini, Rainer and Bergmann, Ralph},
	editor = {Lehner, Franz and N{\"o}sekabel, Holger and Kleinschmidt, Peter},
	month = feb,
	year = {2006},
	pages = {349--361}
}

@inproceedings{minor_flexible_2006-1,
	title = {Flexible {Workflows} for {Digital} {Design} in the {Nano} {Era}},
	url = {http://www.wi2.uni-trier.de/publications/2006_WETICE_MinorEtal.pdf},
	booktitle = {Proceedings of the {Fifteenth} {IEEE} {International} {Workshop} on {Enabling} {Technologies}: {Infrastructure} for {Collaborative} {Enterprises} ({WETICE} 2006), {Workshop} {ProFlex} 2006, {June} 26 - 28, {Manchester}, {UK}},
	publisher = {IEEE Computer Society, Los Alamitos, California},
	author = {Minor, Mirjam and Koldehoff, Andreas and Schmalen, Daniel and Bergmann, Ralph},
	editor = {Weber, Barbara and Mendling, Jan},
	year = {2006},
	pages = {273 -- 278}
}

@inproceedings{bergmann_case-based_2006,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {Case-{Based} {Support} for {Collaborative} {Business}},
	volume = {4106},
	isbn = {3-540-36843-4},
	url = {http://www.wi2.uni-trier.de/publications/2006_ECCBR_bergmann.pdf},
	booktitle = {Advances in {Case}-{Based} {Reasoning}, 8th {European} {Conference}, {ECCBR} 2006, {Fethiye}, {Turkey}, {September} 4-7, 2006, {Proceedings}},
	publisher = {Springer},
	author = {Bergmann, Ralph and Fre{\ss}mann, Andrea and Maximini, Kerstin and Maximini, Rainer and Sauer, Thomas},
	editor = {Roth-Berghofer, Thomas and G{\"o}ker, Mehmet H. and G{\"u}venir, H. Altay},
	year = {2006},
	note = {The original publication is available at www.springerlink.com},
	pages = {519--533}
}

@inproceedings{bergmann_finding_2006,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {Finding {Similar} {Deductive} {Consequences} - {A} {New} {Search}-{Based} {Framework} for {Unified} {Reasoning} from {Cases} and {General} {Knowledge}},
	volume = {4106},
	isbn = {3-540-36843-4},
	url = {http://www.wi2.uni-trier.de/publications/2006_eccbr_bergmann_mougouie_final.pdf},
	booktitle = {Advances in {Case}-{Based} {Reasoning} - {Proceedings} of the 8th {European} {Conference}, {ECCBR} 2006, {Fethiye}, {Turkey}},
	publisher = {Springer},
	author = {Bergmann, Ralph and Mougouie, Babak},
	editor = {Roth-Berghofer, Thomas and G{\"o}ker, Mehmet and G{\"u}venir, H. Altay},
	year = {2006},
	note = {The original publication is available at www.springerlink.com},
	pages = {271--285}
}

@inproceedings{fresmann_collaboration_2005,
	address = {Amsterdam, Netherlands},
	title = {Collaboration {Patterns} for {Adaptive} {Software} {Engineering} {Processes}},
	volume = {135},
	booktitle = {Self-{Organization} and {Autonomic} {Informatics} ({I})},
	publisher = {IOS Press},
	author = {Fre{\ss}mann, Andrea and Sauer, Thomas and Bergmann, Ralph},
	editor = {Czap, Hans and Unland, R. and Branki, C. and Tianfield, H.},
	year = {2005},
	note = {1-58603-577-0},
	pages = {304--312}
}

@article{bergmann_representation_2005,
	title = {Representation in case-based reasoning},
	volume = {20},
	url = {http://journals.cambridge.org/action/displayIssue?jid=KER&volumeId=20&seriesId=0&issueId=03},
	number = {3},
	journal = {The Knowledge Engineering Review},
	author = {Bergmann, Ralph and Kolodner, Janet and Plaza, Enric},
	year = {2005},
	pages = {209--213}
}

@article{cox_case-based_2005,
	title = {Case-based planning},
	volume = {20},
	url = {http://journals.cambridge.org/action/displayIssue?jid=KER&volumeId=20&seriesId=0&issueId=03},
	number = {3},
	journal = {The Knowledge Engineering Review},
	author = {Cox, Michael and Munoz-Avila, Hector and Bergmann, Ralph},
	year = {2005},
	pages = {283--287}
}

@inproceedings{tartakovski_retrieval_2005,
	address = {Chicago, Illinois (USA)},
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {Retrieval and {Configuration} of {Life} {Insurance} {Policies}},
	volume = {3620},
	url = {http://www.wi2.uni-trier.de/publications/2005_ICCBR.pdf},
	booktitle = {Sixth {International} {Conference} on {Case}-{Based} {Reasoning} ({ICCBR} 2005)},
	publisher = {Springer},
	author = {Tartakovski, Alexander and Schaaf, Martin and Bergmann, Ralph},
	editor = {Munoz-Avila, Hector and Ricci, F.},
	year = {2005},
	note = {The original publication is available at www.springerlink.com},
	pages = {552--565}
}

@article{schaaf_intelligent_2004,
	title = {Intelligent {IP} {Retrieval} {Driven} by {Application} {Requirements}},
	volume = {37},
	url = {http://www.wi2.uni-trier.de/publications/2004_VLSI_schaaf.pdf},
	number = {4},
	journal = {Integration, the VLSI Journal},
	author = {Schaaf, Martin and Fre{\ss}mann, Andrea and Maximini, Rainer and Bergmann, Ralph and Tartakovski, Alexander and Radetzki, Martin},
	year = {2004},
	pages = {253--287}
}

@inproceedings{tartakovski_minlp_2004,
	address = {Madrid, Spain},
	series = {{LNAI}},
	title = {{MINLP} {Based} {Retrieval} of {Generalized} {Cases}, {Proceedings} of the 7th {European} {Conference} on {Case} {Based} {Reasoning}, {ECCBR} 2004},
	volume = {3155},
	url = {http://www.wi2.uni-trier.de/publications/2004_tartakovskiECCBR.pdf},
	booktitle = {Advances in {Case}-{Based} {Reasoning}, 7th {European} {Conference}, {ECCBR} 2004, {Madrid}, {Spain}, {August} 30 - {September} 2, 2004},
	publisher = {Springer},
	author = {Tartakovski, Alexander and Schaaf, Martin and Maximini, Rainer and Bergmann, Ralph},
	editor = {Funk, Peter and Calero, Pedro A. Gonz{\'a}lez},
	month = aug,
	year = {2004},
	note = {The original publication is available at www.springerlink.com},
	pages = {404--418}
}

@inproceedings{maximini_investigating_2003,
	series = {{LNI}},
	title = {Investigating different {Methods} for efficient {Retrieval} of {Generalized} {Cases}},
	volume = {28},
	isbn = {3-88579-357-1},
	url = {http://www.wi2.uni-trier.de/publications/2003_gwem.pdf},
	booktitle = {{WM} 2003: {Professionelles} {Wissesmanagement} - {Erfahrungen} und {Visionen}, {Beitr{\"a}ge} der 2. {Konferenz} {Professionelles} {Wissensmanagement}, 2.-4. {April} 2003 in {Luzern}},
	publisher = {GI},
	author = {Maximini, Rainer and Tartakovski, Alexander and Bergmann, Ralph},
	editor = {Reimer, Ulrich and Abecker, Andreas and Staab, Steffen and Stumme, Gerd},
	year = {2003},
	pages = {303--304}
}

@article{bergmann_structural_2003,
	title = {Structural {Case}-{Based} {Reasoning} and {Ontology}-based {Knowledge} {Managemenet}: {A} {Perfect} {Match}?},
	volume = {9},
	url = {http://www.wi2.uni-trier.de/publications/2003_danab_Schaaf_Bergmann.pdf},
	number = {7},
	journal = {Journal of Universal Computer Science},
	author = {Bergmann, Ralph and Schaaf, Martin},
	year = {2003}
}

@book{bergmann_developing_2003,
	edition = {2},
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {Developing {Industrial} {Case}-{Based} {Reasoning} {Applications}: {The} {INRECA} {Methodology}. (2nd {Edition}).},
	volume = {1612},
	url = {http://www.amazon.de/Developing-Industrial-Case-Based-Reasoning-Applications/dp/3540207376/ref=sr_1_1?ie=UTF8&qid=1309873607&sr=8-1},
	publisher = {Springer},
	author = {Bergmann, Ralph and Althoff, Klaus-Dieter and Breen, Sean and G{\"o}ker, Mehmet and Manago, Michel and Traph{\"o}ner, Ralph and Wess, Stefan},
	year = {2003},
	note = {The original publication is available at www.springerlink.com}
}

@inproceedings{bergmann_relations_2003,
	series = {{LNI}},
	title = {On the {Relations} between {Structural} {Case}-{Based} {Reasoning} and {Ontology}-based {Knowledge} {Management}},
	volume = {28},
	url = {http://www.wi2.uni-trier.de/publications/2003_GWEM-OntoCBR-CRC.pdf},
	booktitle = {{WM} 2003: {Professionelles} {Wissesmanagement} - {Erfahrungen} und {Visionen}, {Beitr{\"a}ge} der 2. {Konferenz} {Professionelles} {Wissensmanagement}, 2.-4. {April} 2003 in {Luzern}},
	publisher = {GI},
	author = {Bergmann, Ralph and Schaaf, Martin},
	editor = {Reimer, Ulrich and Abecker, Andreas and Staab, Steffen and Stumme, Gerd},
	year = {2003},
	pages = {279--286}
}

@inproceedings{maximini_investigation_2003,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {An {Investigation} of {Generalized} {Cases}},
	volume = {2689},
	isbn = {3-540-40433-3},
	url = {http://www.wi2.uni-trier.de/publications/2003_ICCBR_maximini.pdf},
	booktitle = {Case-{Based} {Reasoning} {Research} and {Development}, 5th {International} {Conference} on {Case}-{Based} {Reasoning}, {ICCBR} 2003, {Trondheim}, {Norway}, {June} 23-26, 2003, {Proceedings}},
	publisher = {Springer},
	author = {Maximini, Kerstin and Maximini, Rainer and Bergmann, Ralph},
	editor = {Ashley, Kevin D. and Bridge, Derek G.},
	year = {2003},
	note = {The original publication is available at www.springerlink.com},
	pages = {261--275}
}

@inproceedings{mougouie_diversity-conscious_2003,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {Diversity-{Conscious} {Retrieval} from {Generalized} {Cases}: {A} {Branch} and {Bound} {Algorithm}},
	volume = {2989},
	url = {http://www.wi2.uni-trier.de/publications/2003_ICCBR_mougouie.pdf},
	booktitle = {Case-{Based} {Reasoning} {Research} and {Development}, 5th {International} {Conference} on {Case}-{Based} {Reasoning}, {ICCBR} 2003, {Trondheim}, {Norway}, {June} 23-26, 2003},
	publisher = {Springer},
	author = {Mougouie, Babak and Richter, Michael M and Bergmann, Ralph},
	editor = {Ashley, Kevin D and Bridge, Derek},
	year = {2003},
	note = {The original publication is available at www.springerlink.com},
	pages = {319--331}
}

@inproceedings{schaaf_knowledge_2003,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {A {Knowledge} {Representation} {Format} for {Virtual} {IP} {Marketplaces}},
	volume = {2689},
	isbn = {3-540-40433-3},
	url = {http://www.wi2.uni-trier.de/publications/2003_ICCBR_schaaf.pdf},
	booktitle = {Case-{Based} {Reasoning} {Research} and {Development}, 5th {International} {Conference} on {Case}-{Based} {Reasoning}, {ICCBR} 2003, {Trondheim}, {Norway}, {June} 23-26, 2003},
	publisher = {Springer},
	author = {Schaaf, Martin and Fre{\ss}mann, Andrea and Spinelli, Marco A. and Maximini, Rainer and Bergmann, Ralph},
	editor = {Ashley, Kevin D. and Bridge, Derek G.},
	year = {2003},
	note = {The original publication is available at www.springerlink.com},
	pages = {509--521}
}

@inproceedings{wiese_case-based_2003,
	title = {A {Case}-{Based} {Predictive} {Sequencing} {Batch} {Reactor} {Controller}},
	url = {http://www.wi2.uni-trier.de/publications/2003_WieseEtAl_EDSS_IJCAI.pdf},
	booktitle = {18th {International} {Joint} {Conference} on {Artificial} {Intelligence}, {Workshop} on {Environmental} {Decision} {Support} {Systems} ({EDSS}'2003)},
	author = {Wiese, J{\"u}rgen and Schmitt, Sascha and Bergmann, Ralph and Schmitt, Theo G},
	year = {2003}
}

@article{bergmann_acquiring_2002,
	title = {Acquiring {Customers}' {Requirements} in {Electronic} {Commerce}},
	volume = {18},
	url = {http://www.wi2.uni-trier.de/publications/2002_AIRBergCun_fin_.pdf},
	number = {3-4},
	journal = {Artificial Intelligence Review},
	author = {Bergmann, Ralph and Cunningham, P{\'a}draig},
	year = {2002},
	pages = {163--193}
}

@inproceedings{krechel_framework_2002,
	address = {Maribor, Slovenia},
	title = {A {Framework} for {Radiological} {Assistant} {Systems}},
	url = {http://www.wi2.uni-trier.de/publications/2002_cbms.pdf},
	booktitle = {Proceedings of the 15th {IEEE} {Symposium} on {Computer}-based {Medical} {Systems} ({CBMS}'02)},
	publisher = {IEEE Computer Society, Los Alamitos, California},
	author = {Krechel, Dirk and Bergmann, Ralph and Maximini, Kerstin and Wangenheim, Aldo von},
	editor = {Kokol, Peter and Stiglic, Bruno and Zorman, Milan and Zazula, Damjan},
	month = jun,
	year = {2002},
	note = {Best Paper Award},
	pages = {179--184}
}

@inproceedings{stahl_customization_2002,
	title = {A {Customization} {Approach} for {Structured} {Products} in {Electronic} {Shops}},
	url = {http://www.wi2.uni-trier.de/publications/2002_Bled.pdf},
	booktitle = {13th {International} {Bled} {Electronic} {Commerce} {Conference}},
	author = {Stahl, Armin and Bergmann, Ralph and Schmitt, Sascha},
	year = {2002}
}

@inproceedings{bergmann_experience_2002,
	series = {{LNI}},
	title = {Experience {Management} for {Electronic} {Design} {Reuse} through {Quality}-{Oriented} {IP} {Selection}},
	volume = {10},
	isbn = {3-88579-340-7},
	url = {http://www.wi2.uni-trier.de/publications/2002_bergmannmaximinischaaf.pdf},
	booktitle = {1st {German} {Workshop} on {Experience} {Management}: {Sharing} {Experiences} about the {Sharing} of {Experience}, {Berlin}, {March} 7-8, 2002, {Proceedings}},
	publisher = {GI},
	author = {Bergmann, Ralph and Maximini, Rainer and Schaaf, Martin},
	editor = {Minor, Mirjam and Staab, Steffen},
	year = {2002},
	pages = {11--22}
}

@techreport{tautz_prototypical_2002,
	title = {Prototypical implementation of the {Quality} {Related} {Retrieval}. {IPQ} {Deliverable} {AP}2-{T}1-{Q}4},
	institution = {University of Hildesheim},
	author = {Tautz, Carsten and Traph{\"o}ner, Ralph and Bergmann, Ralph and Maximini, Rainer and Schaaf, Martin},
	year = {2002}
}

@techreport{tautz_knowledge_2002,
	title = {Knowledge {Representation} for {IP} {Retrieval}. {IPQ} {Deliverable} {AP}2-{T}2-{Q}4},
	institution = {University of Hildesheim},
	author = {Tautz, Carsten and Traph{\"o}ner, Ralph and Bergmann, Ralph and Maximini, Rainer and Schaaf, Martin},
	year = {2002}
}

@book{bergmann_experience_2002-1,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {Experience {Management}: {Foundations}, {Development} {Methodology}, and {Internet}-{Based} {Applications}},
	volume = {2432},
	url = {http://www.amazon.de/Experience-Management-Foundations-Internet-Based-Applications/dp/3540441913/ref=sr_1_1?ie=UTF8&qid=1309857671&sr=8-1},
	publisher = {Springer},
	author = {Bergmann, Ralph},
	year = {2002},
	note = {The original publication is available at www.springerlink.com}
}

@incollection{bergmann_knowledge-intensive_2002,
	series = {Advanced {Information} {Systems}},
	title = {Knowledge-intensive product search and customization in electronic commerce.},
	url = {http://www.wi2.uni-trier.de/publications/2002_bergmann et al. Buchbeitrag.pdf},
	booktitle = {E-{Business} {Applications}},
	publisher = {Springer},
	author = {Bergmann, Ralph and Traph{\"o}ner, Ralph and Schmitt, Sascha and Cunningham, P{\'a}draig and Smyth, Barry},
	year = {2002},
	note = {The original publication is available at www.springerlink.com},
	pages = {87--101}
}

@incollection{bergmann_intelligent_2002,
	title = {Intelligent customer support for product selection with case-based reasoning.},
	url = {http://www.wi2.uni-trier.de/publications/2002_bergmannschmittstahl.pdf},
	booktitle = {E-{Commerce} and {Intelligent} {Methods}},
	publisher = {Physica-Verlag},
	author = {Bergmann, Ralph and Schmitt, Sascha and Stahl, Armin},
	editor = {Segovia, J. and Szezepaniak, P. and Niedzwiedzinski, M.},
	year = {2002},
	pages = {322--341}
}

@inproceedings{mougouie_similarity_2002,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {Similarity {Assessment} for {Generalized} {Cases} by {Optimization} {Methods}},
	volume = {2416},
	url = {http://www.wi2.uni-trier.de/publications/2002_ECCBR_mougouie.pdf},
	booktitle = {European {Conference} on {Case}-{Based} {Reasoning} ({ECCBR}'02)},
	publisher = {Springer},
	author = {Mougouie, Babak and Bergmann, Ralph},
	editor = {Craw, S. and Preece, A.},
	year = {2002},
	note = {The original publication is available at www.springerlink.com},
	pages = {249--263}
}

@inproceedings{schaaf_supporting_2002,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {Supporting {Electronic} {Design} {Reuse} by {Integrating} {Quality}-{Criteria} into {CBR}-{Based} {IP} {Selection}},
	volume = {2416},
	isbn = {3-540-44109-3},
	url = {http://www.wi2.uni-trier.de/publications/2002_eccbr.pdf},
	booktitle = {Advances in {Case}-{Based} {Reasoning}, 6th {European} {Conference}, {ECCBR} 2002 {Aberdeen}, {Scotland}, {UK}, {September} 4-7, 2002, {Proceedings}},
	publisher = {Springer},
	author = {Schaaf, Martin and Maximini, Rainer and Bergmann, Ralph and Tautz, Carsten and Traph{\"o}ner, Ralph},
	editor = {Craw, Susan and Preece, Alun D.},
	year = {2002},
	note = {The original publication is available at www.springerlink.com},
	pages = {628--641}
}

@incollection{schaaf_ipchl_2002,
	title = {{IPCHL} - {A} {Description} {Language} for {Semantic} {IP} {Characterization}},
	url = {http://www.wi2.uni-trier.de/publications/2002_fdl.pdf},
	booktitle = {Best of {FDL}'02, {System} {Specification} \& {Design} {Languages}},
	author = {Schaaf, Martin and Visarius, Markus and Bergmann, Ralph and Maximini, Rainer and Spinelli, Marco and Lessmann, Johannes and Hardt, Wolfram and Thronicke, Wolfgang and Franz, Jasmin and Tautz, Carsten and Traph{\"o}ner, Ralph},
	month = sep,
	year = {2002}
}

@inproceedings{kohlmaier_evaluation_2001,
	title = {Evaluation of a similarity-based approach to customer-adaptive electronic sales dialogs},
	url = {http://www.wi2.uni-trier.de/publications/2001_kohlmaier_et_al.pdf},
	booktitle = {Workshop on {Empirical} {Evaluations} of {Adaptive} {Systems}},
	author = {Kohlmaier, Andreas and Schmitt, Sascha and Bergmann, Ralph},
	editor = {Weibelzahl, Stephan and Chin, David and Weber, Gehard},
	month = jul,
	year = {2001},
	pages = {41--50}
}

@techreport{tautz_concepts_2001,
	title = {Concepts for the {Integration} of {IP} {Quality} {Criteria} into {IP} {Characterization} and {Retrieval}. {IPQ} {Deliverable} {AP}2-{T}1-{Q}2},
	institution = {University of Kaiserslautern},
	author = {Tautz, Carsten and Traph{\"o}ner, Ralph and Bergmann, Ralph and Maximini, Rainer and Schaaf, Martin and Vollrath, Ivo},
	year = {2001}
}

@inproceedings{schmitt_formal_2001,
	title = {A {Formal} {Approach} to {Dialogs} with {Online} {Customers}},
	url = {http://www.wi2.uni-trier.de/publications/2001_schmittbergmann2001.pdf},
	booktitle = {Proc. of the 14 th {Bled} {Electronic} {Commerce} {Conference}},
	author = {Schmitt, Sascha and Bergmann, Ralph},
	year = {2001}
}

@inproceedings{bergmann_utility-oriented_2001,
	title = {Utility-{Oriented} {Matching}: {A} {New} {Research} {Direction} for {Case}-{Based} {Reasoning}},
	url = {http://www.wi2.uni-trier.de/publications/2001_bergmannrichter.pdf},
	booktitle = {9th {German} {Workshop} on {Case}-{Based} {Reasoning} ({GWCBR}'2001)},
	author = {Bergmann, Ralph and Richter, Michael M and Schmitt, Sascha and Stahl, Armin and Vollrath, Ivo},
	year = {2001}
}

@techreport{tautz_requirements_2001,
	title = {Requirements on {IP} {Qualifying} {Format}. {IPQ} {Deliverable} {AP}1-{T}1-{Q}2},
	institution = {University of Kaiserslautern},
	author = {Tautz, Carsten and Traph{\"o}ner, Ralph and R{\"u}lke, Stefan and Martinez, N. and Seepolt, Ralf and V{\"o}rg, A. and Radetzki, Martin and Thronicke, Wolfgang and Jerinic, V. and M{\"u}ller, D. and Siegmund, M. and Bergmann, Ralph and Vollrath, Ivo and Schaaf, Martin},
	year = {2001}
}

@inproceedings{cunningham_intelligent_2001,
	title = {Intelligent {Support} for {Online} {Sales}: {The} {WEBSELL} {Experience}},
	url = {http://www.wi2.uni-trier.de/publications/2001_cunninghambergmann.pdf},
	booktitle = {Proceedings of the {Workshop} {Program} at the {Fourth} {International} {Conference} on {Case}-{Based} {Reasoning} ({ICCBR} 2001)},
	author = {Cunningham, P{\'a}draig and Bergmann, Ralph and Schmitt, Sascha and Traph{\"o}ner, Ralph and Breen, Sean and Smyth, Barry},
	editor = {Weber, R. and Wangenheim, Christiane Gresse von},
	year = {2001},
	note = {Proceedings of the ECAI'2000 Workshop on Flexible Strategies for Maintaining Knowledge Containers}
}

@inproceedings{bergmann_highlights_2001,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {Highlights of the {European} {INRECA} {Projects}},
	volume = {2080},
	isbn = {3-540-42358-3},
	url = {http://www.wi2.uni-trier.de/publications/2001_Bergmann Inreca ICCBR.pdf},
	booktitle = {Case-{Based} {Reasoning} {Research} and {Development}, 4th {International} {Conference} on {Case}-{Based} {Reasoning}, {ICCBR} 2001, {Vancouver}, {BC}, {Canada}, {July} 30 - {August} 2, 2001, {Proceedings}},
	publisher = {Springer},
	author = {Bergmann, Ralph},
	editor = {Aha, David W. and Watson, Ian},
	year = {2001},
	note = {The original publication is available at www.springerlink.com},
	pages = {1--15}
}

@inproceedings{kohlmaier_similarity-based_2001,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {A {Similarity}-{Based} {Approach} to {Attribute} {Selection} in {User}-{Adaptive} {Sales} {Dialogs}},
	volume = {2080},
	isbn = {3-540-42358-3},
	url = {http://www.wi2.uni-trier.de/publications/2001_akohlmaier.pdf},
	booktitle = {Case-{Based} {Reasoning} {Research} and {Development}, 4th {International} {Conference} on {Case}-{Based} {Reasoning}, {ICCBR} 2001, {Vancouver}, {BC}, {Canada}, {July} 30 - {August} 2, 2001, {Proceedings}},
	publisher = {Springer},
	author = {Kohlmaier, Andreas and Schmitt, Sascha and Bergmann, Ralph},
	editor = {Aha, David W. and Watson, Ian},
	year = {2001},
	note = {The original publication is available at www.springerlink.com},
	pages = {306--320}
}

@article{cunningham_websell:_2001,
	title = {{WEBSELL}: {Intelligent} {Sales} {Assistants} for the {World} {Wide} {Web}},
	volume = {15},
	url = {http://www.wi2.uni-trier.de/publications/2001_KI Websell.pdf},
	number = {1},
	journal = {KI - K{\"u}nstliche Intelligenz},
	author = {Cunningham, Padraig and Bergmann, Ralph and Schmitt, Sascha and Traph{\"o}ner, Ralph and Breen, Sean and Smyth, Barry},
	year = {2001},
	pages = {28--32}
}

@inproceedings{stahl_customization_2000,
	title = {A {Customization} {Approach} for {Structured} {Products} in {Electronic} {Shops}},
	url = {http://www.wi2.uni-trier.de/publications/2000_bled.pdf},
	booktitle = {in {Proceedings} of the {Thirteenth} {Bled} {Electronic} {Commerce} {Conference}},
	author = {Stahl, Armin and Bergmann, Ralph and Schmitt, Sascha},
	year = {2000},
	pages = {252--264}
}

@inproceedings{koegst_utilizing_2000,
	address = {Rathen},
	title = {Utilizing {Constraint} {Satisfaction} {Approaches} for {IP} {Retrieval}},
	url = {http://www.wi2.uni-trier.de/publications/2000_sda.pdf},
	booktitle = {3rd {Workshop} on {System} {Design} {Automation}},
	author = {Koegst, M. and Schneider, J. and Bergmann, Ralph and Vollrath, Ivo},
	year = {2000}
}

@inproceedings{schumacher_similarity-based_2000,
	title = {Similarity-based retrieval on top of relational databases},
	booktitle = {Case-{Based} {Reasoning}: {Papers} from the {Eighth} {German} {Workshop}. {L{\"a}mmerbuckel}, {Germany}: {DaimlerChrysler} {Research} and {Technology}},
	author = {Schumacher, J{\"u}rgen and Bergmann, Ralph},
	editor = {G{\"o}ker, Mehmet},
	year = {2000}
}

@inproceedings{stahl_applying_2000,
	title = {Applying recursive {CBR} for the customization of structured products in an electronic shop},
	booktitle = {Case-{Based} {Reasoning}: {Papers} from the {Eighth} {German} {Workshop}. {L{\"a}mmerbuckel}, {Germany}: {DaimlerChrysler} {Research} and {Technology}},
	author = {Stahl, Armin and Bergmann, Ralph},
	editor = {G{\"o}ker, Mehmet},
	year = {2000}
}

@inproceedings{stahl_applying_2000-1,
	series = {Lecture {Notes} in {Computer} {Science}},
	title = {Applying {Recursive} {CBR} for the {Custumization} of {Structured} {Products} in an {Electronic} {Shop}},
	volume = {1898},
	isbn = {3-540-67933-2},
	url = {http://www.wi2.uni-trier.de/publications/2000_ewcbr_stahl_bergmann.pdf},
	booktitle = {Advances in {Case}-{Based} {Reasoning}, 5th {European} {Workshop}, {EWCBR} 2000, {Trento}, {Italy}, {September} 6-9, 2000, {Proceedings}},
	publisher = {Springer},
	author = {Stahl, Armin and Bergmann, Ralph},
	editor = {Blanzieri, Enrico and Portinale, Luigi},
	year = {2000},
	note = {The original publication is available at www.springerlink.com},
	pages = {297--308}
}

@inproceedings{schumacher_efficient_2000,
	series = {Lecture {Notes} in {Computer} {Science}},
	title = {An {Efficient} {Approach} to {Similarity}-{Based} {Retrieval} on {Top} of {Relational} {Databases}},
	volume = {1898},
	isbn = {3-540-67933-2},
	url = {http://www.wi2.uni-trier.de/publications/2000_ewcbr_retrieval.pdf},
	booktitle = {Advances in {Case}-{Based} {Reasoning}, 5th {European} {Workshop}, {EWCBR} 2000, {Trento}, {Italy}, {September} 6-9, 2000, {Proceedings}},
	publisher = {Springer},
	author = {Schumacher, J{\"u}rgen and Bergmann, Ralph},
	editor = {Blanzieri, Enrico and Portinale, Luigi},
	year = {2000},
	note = {The original publication is available at www.springerlink.com},
	pages = {273--284}
}

@inproceedings{weibelzahl_towards_2000,
	title = {Towards an empirical evaluation of {CBR} approaches for product recommendeation in electronic shops},
	url = {http://www.wi2.uni-trier.de/publications/2000_gwcbr_weibelzahl_bergmann.pdf},
	booktitle = {Case-{Based} {Reasoning}: {Papers} from the {Eighth} {German} {Workshop}. {L{\"a}mmerbuckel}, {Germany}: {DaimlerChrysler} {Research} and {Technology}},
	author = {Weibelzahl, Stephan and Bergmann, Ralph and Weber, Gerhard},
	editor = {G{\"o}ker, Mehmet},
	year = {2000}
}

@inproceedings{bergmann_generalized_1999,
	title = {Generalized cases and their application to electronic designs},
	url = {http://www.wi2.uni-trier.de/publications/1999_GeneralizedCasesGWCBR.pdf},
	booktitle = {7th {German} {Workshop} on {Case}-{Based} {Reasoning}},
	author = {Bergmann, Ralph and Vollrath, Ivo and Wahlmann, T.},
	editor = {Melis, E.},
	year = {1999}
}

@inproceedings{schmitt_product_1999,
	title = {Product customization in an electronic commerce environment using adaptation operators},
	url = {http://www.wi2.uni-trier.de/publications/1999_schmittbergmann99.pdf},
	booktitle = {7th {German} {Workshop} on {Case}-{Based} {Reasoning}},
	author = {Schmitt, Sascha and Bergmann, Ralph},
	editor = {Melis, E.},
	year = {1999}
}

@inproceedings{hullen_webplan:_1999,
	title = {{WebPlan}: {Dynamic} planning for domain-specific search in the {Internet}},
	url = {http://www.wi2.uni-trier.de/publications/1999_PuKPaper.pdf},
	booktitle = {13. {Workshop} "{Planen} und {Konfigurieren}" ({PuK}-99)},
	author = {H{\"u}llen, Jochem and Bergmann, Ralph and Weberskirch, Frank},
	editor = {K{\"o}hler, J.},
	year = {1999}
}

@inproceedings{schmitt_applying_1999,
	title = {Applying case-based reasoning technology for product selection and customization in electronic commerce environments},
	url = {http://www.wi2.uni-trier.de/publications/1999_PaperBled.pdf},
	booktitle = {12th {Bled} {Electronic} {Commerce} {Conference}},
	author = {Schmitt, Sascha and Bergmann, Ralph},
	year = {1999}
}

@inproceedings{bergmann_developing_1999,
	title = {Developing {Industrial} {Case}-{Based} {Reasoning} {Applications} {Using} the {INRECA} {Methodology}},
	url = {http://www.wi2.uni-trier.de/publications/1999_ijcai.pdf},
	booktitle = {{IJCAI}-99 {Workshop} on the automatic construction of case-based reasoners},
	author = {Bergmann, Ralph and G{\"o}ker, Mehmet},
	editor = {Anand, S.S. and Aamodt, A. and Aha, D.},
	year = {1999}
}

@techreport{bergmann_design_1999,
	title = {Design of the intelligent sales architecture, {WEBSELL} {Deliverables} {D}3.1 \& {D}4.1. {WEBSELL} {Consortium}},
	institution = {University of Kaiserslautern},
	author = {Bergmann, Ralph and Breen, Sean and Cunningham, P{\'a}draig and Dobal, R. and Grohmann, H. -J and McNaulty, P. and Schmitt, Sascha and Traph{\"o}ner, Ralph and Voltz, M. and Wolf, Max},
	year = {1999}
}

@book{bergmann_developing_1999-1,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {Developing {Industrial} {Case}-{Based} {Reasoning} {Applications}: {The} {INRECA} {Methodology}.},
	volume = {1612},
	url = {http://www.springer.com/computer/ai/book/978-3-540-20737-5},
	publisher = {Springer},
	author = {Bergmann, Ralph and Breen, Sean and G{\"o}ker, Mehmet and Manago, Michel and Wess, Stefan},
	year = {1999},
	note = {The original publication is available at www.springerlink.com}
}

@inproceedings{bergmann_generalized_1999-1,
	series = {Lecture {Notes} in {Artificial} {Intelligence}},
	title = {Generalized {Cases}: {Representation} and {Steps} {Towards} {Efficient} {Similarity} {Assessment}},
	volume = {1701},
	url = {http://www.wi2.uni-trier.de/publications/1999_ki.pdf},
	booktitle = {Proceedings of the 23rd {Annual} {German} {Conference} on {Artificial} {Intelligence}: {Advances} in {Artificial} {Intelligence}},
	publisher = {Springer},
	author = {Bergmann, Ralph and Vollrath, Ivo},
	editor = {Burgard, W. and Christaller, Th. and Cremers, A.B.},
	year = {1999},
	note = {The original publication is available at www.springerlink.com},
	pages = {195--206}
}

@inproceedings{koegst_ip_1999,
	title = {{IP} {Retrieval} by solving constraint satisfaction problems},
	url = {http://www.wi2.uni-trier.de/publications/1999_Koegst_Lyon.pdf},
	booktitle = {{FDL} '99, {Second} {International} {Forum} on {Design} {Languages}},
	author = {Koegst, M. and Schneider, J. and Bergmann, Ralph and Vollrath, Ivo},
	year = {1999}
}

@article{bergmann_preface_1999,
	title = {Preface to the special issue on {Engineering} {Applications} of {Case}-{Based} {Reasoning}},
	volume = {12},
	url = {http://www.wi2.uni-trier.de/publications/1999_Preface_EAAI.pdf},
	number = {6},
	journal = {Engineering Applications of Artificial Intelligence},
	author = {Bergmann, Ralph},
	year = {1999},
	note = {Elsevier},
	pages = {661--663}
}

@inproceedings{bergmann_efficient_1998,
	title = {Efficient {Retrieval} of {Abstract} {Cases} for {Case}-{Based} {Planning}},
	url = {http://www.wi2.uni-trier.de/publications/1998_sara_bergmann.pdf},
	booktitle = {Proceedings of the {Symposium} on {Abstraction}, {Reformulation} and {Approximation} ({SARA}'98)},
	publisher = {Rutgers University},
	author = {Bergmann, Ralph},
	year = {1998},
	pages = {9--18}
}

@inproceedings{wilke_negotiation_1998,
	title = {Negotiation {During} {Intelligent} {Sales} {Support} with {Case}-{Based} {Reasoning}},
	url = {http://www.wi2.uni-trier.de/publications/1998_Negotiation_wilke_atall.pdf},
	booktitle = {Proceedings of the 6th {German} {Workshop} on {Case}-{Based} {Reasoning} ({GWCBR}'98)},
	author = {Wilke, Wolfgang and Bergmann, Ralph and Wess, Stefan},
	editor = {Gierl, Lothar and Lenz, Mario},
	year = {1998}
}

@inproceedings{bergmann_inreca-ii_1998,
	title = {The {INRECA}-{II} {Methodology} for {Building} and {Maintaining} {CBR} {Applications}},
	url = {http://www.wi2.uni-trier.de/publications/1998_INRECA GWCBR.pdf},
	booktitle = {Proceedings of the 6th {German} {Workshop} on {Case}-{Based} {Reasoning} ({GWCBR}'98)},
	author = {Bergmann, Ralph and Breen, Sean and G{\"o}ker, Mehmet and Manago, Michel and Schmitt, Sascha and Schumacher, J{\"u}rgen and Stahl, Armin and Tartarin, Emmanuelle and Wess, Stefan and Wilke, Wolfgang},
	editor = {Gierl, Lothar and Lenz, Mario},
	year = {1998}
}

@inproceedings{bergmann_towards_1998,
	title = {Towards a {New} {Formal} {Model} of {Transformational} {Adaptation} in {Case}-{Based} {Reasoning}},
	url = {http://www.wi2.uni-trier.de/publications/1998_ecai.pdf},
	booktitle = {13th {European} {Conference} on {Artificial} {Intelligence} ({ECAI}'98)},
	publisher = {John Wiley \& Sons},
	author = {Bergmann, Ralph and Wilke, Wolfgang},
	editor = {Prade, Henry},
	year = {1998},
	pages = {53--57}
}

@inproceedings{bergmann_use_1998,
	title = {On the {Use} of {Taxonomies} for {Representing} {Case} {Features} and {Local} {Similarity} {Measures}},
	url = {http://www.wi2.uni-trier.de/publications/1998_BergmannGwcbr.pdf},
	booktitle = {Proceedings of the 6th {German} {Workshop} on {Case}-{Based} {Reasoning} ({GWCBR}'98)},
	author = {Bergmann, Ralph},
	editor = {Gierl, Lothar and Lenz, Mario},
	year = {1998}
}

@article{althoff_case-based_1998,
	title = {Case-{Based} {Reasoning} for {Medical} {Decision} {Support} {Tasks}: {The} {INRECA} {Approach}},
	volume = {12},
	url = {http://www.wi2.uni-trier.de/publications/1998_AI_in_med.pdf},
	number = {1},
	journal = {Artificial Intelligence in Medicine Journal (AIMJ)},
	author = {Althoff, Klaus-Dieter and Bergmann, Ralph and Wess, Stefan and Manago, Michel and Auriol, Eric and Larichev, O. and Bolotov, Alexander and Zhuravlev, Yurii I and Gurov, Serge I},
	year = {1998},
	pages = {25--41}
}

@techreport{manago_specification_1998,
	title = {Specification of tools that support the methodology. {INRECA}-{II} {Deliverable} {D}7, {INRECA} {Consortium}},
	institution = {University of Kaiserslautern},
	author = {Manago, Michel and Bergmann, Ralph and Stahl, Armin and Wilke, Wolfgang},
	year = {1998}
}

@techreport{bergmann_refined_1998,
	title = {Refined methodology for building and maintaining a {CBR} application. {ESPRIT}-{Project} {INRECA}-{II}, {Deliverable} {D}6, {INRECA} {Consortium}},
	institution = {University of Kaiserslautern},
	author = {Bergmann, Ralph and Breen, Sean and Fayol, E. and G{\"o}ker, Mehmet and Johnston, Roy and Schmitt, Sascha and Schumacher, J{\"u}rgen and Stahl, Armin and Traph{\"o}ner, Ralph and Wess, Stefan and Wilke, Wolfgang},
	year = {1998}
}

@inproceedings{wilke_techniques_1998,
	series = {Lecture {Notes} in {Computer} {Science}},
	title = {Techniques and knowledge used for adaptation during base-cased problem solving},
	volume = {1416},
	isbn = {3-540-64574-8},
	url = {http://www.wi2.uni-trier.de/publications/1998_wilketechniques.pdf},
	booktitle = {Tasks and {Methods} in {Applied} {Artificial} {Intelligence}, 11th {International} {Conference} on {Industrial} and {Engineering} {Applications} of {Artificial} {In} telligence and {Expert} {Systems}, {IEA}/{AIE}-98, {Castell{\'o}n}, {Spain}, {June} 1-4, 1998, {Proceedings}, {Volume} {II}},
	publisher = {Springer},
	author = {Wilke, Wolfgang and Bergmann, Ralph},
	editor = {Pobil, Angel P. Del and Mira, Jos{\'e} and Ali, Moonis},
	year = {1998},
	note = {The original publication is available at www.springerlink.com},
	pages = {497--506}
}

@inproceedings{vollrath_intelligent_1998,
	address = {Springer},
	title = {Intelligent {Electronic} {Catalogs} for {Sales} {Support} - {Introducing} {Case}-{Based} {Reasoning} {Techniques} to {On}-{Line} {Product} {Selection} {Applications}},
	url = {http://www.wi2.uni-trier.de/publications/1998_Catalogs.pdf},
	booktitle = {Proceedings of the 3rd {World} {Conference} on {Soft} {Computing}: {Advances} in {Soft} {Computing} - {Engineering} {Design} and {Manufacturing}},
	author = {Vollrath, Ivo and Wilke, Wolfgang and Bergmann, Ralph},
	editor = {Roy, R. and Furuhashi, T. and Chawddhry, P.K.},
	year = {1998},
	note = {The original publication is available at www.springerlink.com}
}

@inproceedings{goker_development_1998,
	series = {Lecture {Notes} in {Computer} {Science}},
	title = {The {Development} of {HOMER}: {A} {Case}-{Based} {CAD}/{CAM} {Help}-{Desk} {Support} {Tool}},
	volume = {1488},
	isbn = {3-540-64990-5},
	url = {http://www.wi2.uni-trier.de/publications/1998_homer_ewcbr.pdf},
	booktitle = {Advances in {Case}-{Based} {Reasoning}, 4th {European} {Workshop}, {EWCBR}-98, {Dublin}, {Ireland}, {September} 1998, {Proceedings}},
	publisher = {Springer},
	author = {G{\"o}ker, Mehmet H. and Roth-Berghofer, Thomas and Bergmann, Ralph and Pantleon, Thomas and Traph{\"o}ner, Ralph and Wess, Stefan and Wilke, Wolfgang},
	editor = {Smyth, Barry and Cunningham, Padraig},
	year = {1998},
	note = {The original publication is available at www.springerlink.com},
	pages = {346--357}
}

@inproceedings{bergmann_similarity_1998,
	series = {Lecture {Notes} in {Computer} {Science}},
	title = {Similarity {Measures} for {Object}-{Oriented} {Case} {Representations}},
	volume = {1488},
	isbn = {3-540-64990-5},
	url = {http://www.wi2.uni-trier.de/publications/1998_EWCBR98_similarity_CRC.pdf},
	booktitle = {Advances in {Case}-{Based} {Reasoning}, 4th {European} {Workshop}, {EWCBR}-98, {Dublin}, {Ireland}, {September} 1998, {Proceedings}},
	publisher = {Springer},
	author = {Bergmann, Ralph and Stahl, Armin},
	editor = {Smyth, Barry and Cunningham, Padraig},
	year = {1998},
	note = {The original publication is available at www.springerlink.com},
	pages = {25--36}
}

@inproceedings{bergmann_collecting_1998,
	series = {Lecture {Notes} in {Computer} {Science}},
	title = {Collecting {Experience} on the {Systematic} {Development} of {CBR} {Applications} {Using} the {INRECA} {Methodology}},
	volume = {1488},
	isbn = {3-540-64990-5},
	url = {http://www.wi2.uni-trier.de/publications/1998_bergmann_ewcbr_collecting.pdf},
	booktitle = {Advances in {Case}-{Based} {Reasoning}, 4th {European} {Workshop}, {EWCBR}-98, {Dublin}, {Ireland}, {September} 1998, {Proceedings}},
	publisher = {Springer},
	author = {Bergmann, Ralph and Breen, Sean and Fayol, Emmanuelle and G{\"o}ker, Mehmet H. and Manago, Michel and Schmitt, Sascha and Schumacher, J{\"u}rgen and Stahl, Armin and Wess, Stefan and Wilke, Wolfgang},
	editor = {Smyth, Barry and Cunningham, Padraig},
	year = {1998},
	note = {The original publication is available at www.springerlink.com},
	pages = {460--470}
}

@inproceedings{bergmann_towards_1998-1,
	title = {Towards a {New} {Formal} {Model} of {Transformational} {Adaptation} in {Case}-{Based} {Reasoning}},
	booktitle = {Proceedings of the 6th {German} {Workshop} on {Case}-{Based} {Reasoning} ({GWCBR}'98)},
	author = {Bergmann, Ralph and Wilke, Wolfgang},
	year = {1998}
}

@article{vollrath_case-based_1998,
	title = {Case-based reasoning support for online catalog sales},
	volume = {2},
	issn = {1089-7801},
	url = {http://www.wi2.uni-trier.de/publications/1998_w4voll.pdf},
	doi = {10.1109/4236.707690},
	number = {4},
	journal = {Internet Computing, IEEE},
	author = {Vollrath, I. and Wilke, W. and Bergmann, R.},
	month = aug,
	year = {1998},
	keywords = {based, catalog, catalogs;electronic, commerce;information, data, Internet;case-based, knowledge;electronic, measures;Internet;case-based, processing;, reasoning;databases;domain-specific, reasoning;knowledge, retrieval;intelligent, sales, sales;problem, solving;similarity, support;online, systems;marketing},
	pages = {47 --54}
}

@inproceedings{carranza_proposal_1998,
	title = {Proposal for a planning approach for information seeking},
	volume = {98},
	url = {http://www.wi2.uni-trier.de/publications/1998_Carranza_etal.pdf},
	booktitle = {{AIPS}'98 {Workshop} on {Integrating} {Planning}, {Scheduling} and {Execution} in {Dynamic} and {Uncertain} {Environments}},
	publisher = {AAAI Press},
	author = {Carranza, C. and Munoz-Avila, H. and Weberskirch, F. and Bergmann, R.},
	editor = {Bergmann, Ralph and Kott, Alexander},
	year = {1998}
}

@inproceedings{oehler_are_1998,
	series = {{FZI}-{Report}},
	title = {Are your {READee} for {IPs}?},
	url = {http://www.wi2.uni-trier