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\n  \n 2026\n \n \n (10)\n \n \n
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\n \n\n \n \n \n \n \n A Machine Learning Approach Using Open Databases to Support Drug Delivery Prediction.\n \n \n \n\n\n \n Pestana, H.; Regino, A. G.; Dametto, M.; Zagatti, F. R.; and Bonacin, R.\n\n\n \n\n\n\n In Costin, H.; Magjarevic, R.; and Petroiu, G., editor(s), Advances in Digital Health and Medical Bioengineering II, pages 484–490, Cham, 2026. Springer Nature Switzerland\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{10.1007/978-3-032-24724-7_49,\n  author = {Pestana, Helder and Regino, Andr{\\'e} Gomes and Dametto, Mariangela and Zagatti, Fernando Rezende and Bonacin, Rodrigo},\n  editor = {Costin, Hariton-Nicolae and Magjarevic, Ratko and Petroiu, Gabriela-Gladiola},\n  title = {A Machine Learning Approach Using Open Databases to Support Drug Delivery Prediction},\n  booktitle = {Advances in Digital Health and Medical Bioengineering II},\n  year = {2026},\n  publisher = {Springer Nature Switzerland},\n  address = {Cham},\n  pages = {484--490},\n  abstract = {The development of effective and safe drugs is a complex and resource-intensive process that often relies on uncertain trial-and-error methods. Predicting pharmacokinetic properties, such as drug delivery, is decisive for accelerating drug discovery and enhancing therapeutic outcomes. This paper presents a Machine Learning (ML) and Deep Learning (DL) based approach utilizing open pharmacological databases to predict properties associated with drug distribution, with a focus on bioavailability and the octanol-water partition coefficient (LogP). The study encompasses data preprocessing, molecular representation via SMILES encoding, and model evaluation utilizing regression and classification metrics. Results show promising predictive performance, suggesting that ML and DL techniques can optimize early drug discovery stages and support decision-making.},\n  isbn = {978-3-032-24724-7},\n  doi = {10.1007/978-3-032-24724-7_49},\n}\n\n
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\n The development of effective and safe drugs is a complex and resource-intensive process that often relies on uncertain trial-and-error methods. Predicting pharmacokinetic properties, such as drug delivery, is decisive for accelerating drug discovery and enhancing therapeutic outcomes. This paper presents a Machine Learning (ML) and Deep Learning (DL) based approach utilizing open pharmacological databases to predict properties associated with drug distribution, with a focus on bioavailability and the octanol-water partition coefficient (LogP). The study encompasses data preprocessing, molecular representation via SMILES encoding, and model evaluation utilizing regression and classification metrics. Results show promising predictive performance, suggesting that ML and DL techniques can optimize early drug discovery stages and support decision-making.\n
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\n \n\n \n \n \n \n \n LLM-Based Solution Applied to Explore Healthcare Datasets.\n \n \n \n\n\n \n Zagatti, F. R.; Regino, A. G.; Lopes, F. L.; Shimizu, G. Y.; Bonacin, R.; Lucrédio, D.; and de Medeiros Caseli, H.\n\n\n \n\n\n\n In Costin, H.; Magjarevic, R.; and Petroiu, G., editor(s), Advances in Digital Health and Medical Bioengineering II, pages 525–530, Cham, 2026. Springer Nature Switzerland\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{10.1007/978-3-032-24724-7_53,\n  author = {Zagatti, Fernando Rezende and Regino, Andr{\\'e} Gomes and Lopes, Filipe Loyola and Shimizu, Gilson Yuuji and Bonacin, Rodrigo and Lucr{\\'e}dio, Daniel and de Medeiros Caseli, Helena},\n  editor = {Costin, Hariton-Nicolae and Magjarevic, Ratko and Petroiu, Gabriela-Gladiola},\n  title = {LLM-Based Solution Applied to Explore Healthcare Datasets},\n  booktitle = {Advances in Digital Health and Medical Bioengineering II},\n  year = {2026},\n  publisher = {Springer Nature Switzerland},\n  address = {Cham},\n  pages = {525--530},\n  abstract = {The growing availability of open health datasets has advanced medical research and healthcare innovation. This study proposes a Large Language Model (LLM) approach that enables Exploratory Data Analysis (EDA) through natural language queries by integrating Retrieval-Augmented Generation (RAG) and post-processing mechanisms. It was evaluated using five open health datasets, encompassing both structured and unstructured data. The results show that the approach effectively describes datasets, identifies outliers, and produces diverse visualizations, including histograms and correlation heatmaps. The method demonstrates the feasibility of using LLMs to automate and democratize EDA, enhancing accessibility and interpretability in health data exploration.},\n  isbn = {978-3-032-24724-7},\n  doi = {10.1007/978-3-032-24724-7_53},\n}\n\n
\n
\n\n\n
\n The growing availability of open health datasets has advanced medical research and healthcare innovation. This study proposes a Large Language Model (LLM) approach that enables Exploratory Data Analysis (EDA) through natural language queries by integrating Retrieval-Augmented Generation (RAG) and post-processing mechanisms. It was evaluated using five open health datasets, encompassing both structured and unstructured data. The results show that the approach effectively describes datasets, identifies outliers, and produces diverse visualizations, including histograms and correlation heatmaps. The method demonstrates the feasibility of using LLMs to automate and democratize EDA, enhancing accessibility and interpretability in health data exploration.\n
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\n \n\n \n \n \n \n \n Digital Technologies, Challenges, and Strategies in Distance Education: A Study with Students from a Brazilian Public University.\n \n \n \n\n\n \n Regino, A. G.; Shimizu, G. Y.; Zagatti, F. R.; Lopes, F. L.; Caceffo, R. E.; Bonacin, R.; and dos Reis, J. C.\n\n\n \n\n\n\n In Sprock, A. S.; Bezeira, A. M.; and Agredo-Delgado, V., editor(s), Proceedings of the 20th Latin American Conference on Learning Technologies (LACLO 2025), pages 258–272, Singapore, 2026. Springer Nature Singapore\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{10.1007/978-981-95-7580-0_19,\n  author = {Regino, André Gomes and Shimizu, Gilson Yuuji and Zagatti, Fernando Rezende and Lopes, Filipe Loyola and Caceffo, Ricardo Edgard and Bonacin, Rodrigo and dos Reis, Julio Cesar},\n  editor = {Sprock, Antonio Silva and Bezeira, Ana Morales and Agredo-Delgado, Vanessa},\n  title = {Digital Technologies, Challenges, and Strategies in Distance Education: A Study with Students from a Brazilian Public University},\n  booktitle = {Proceedings of the 20th Latin American Conference on Learning Technologies (LACLO 2025)},\n  year = {2026},\n  publisher = {Springer Nature Singapore},\n  address = {Singapore},\n  pages = {258--272},\n  abstract = {Distance education at scale presents unique opportunities and challenges, especially in public systems designed for broad access. The goal of this study is to explore how students engage with educational technologies and navigate online learning, using data from a Brazilian statewide virtual university. We investigate usage patterns, learning difficulties, and the early adoption of emerging tools (e.g., ChatGPT). Our methodology combines both statistical analysis and topic modeling to uncover behavioral profiles and factors influencing engagement. The results reveal distinct trends across age groups and academic areas, including a counterintuitive finding: younger students, often seen as digital natives, reported more difficulty with focus and engagement than older peers. These patterns suggest the existence of at-risk profiles that can benefit from targeted support strategies. Our findings offer practical implications for improving online learning experiences and inform future research on how digital platforms and AI tools can support inclusive, flexible education in public settings.},\n  isbn = {978-981-95-7580-0},\n}\n\n
\n
\n\n\n
\n Distance education at scale presents unique opportunities and challenges, especially in public systems designed for broad access. The goal of this study is to explore how students engage with educational technologies and navigate online learning, using data from a Brazilian statewide virtual university. We investigate usage patterns, learning difficulties, and the early adoption of emerging tools (e.g., ChatGPT). Our methodology combines both statistical analysis and topic modeling to uncover behavioral profiles and factors influencing engagement. The results reveal distinct trends across age groups and academic areas, including a counterintuitive finding: younger students, often seen as digital natives, reported more difficulty with focus and engagement than older peers. These patterns suggest the existence of at-risk profiles that can benefit from targeted support strategies. Our findings offer practical implications for improving online learning experiences and inform future research on how digital platforms and AI tools can support inclusive, flexible education in public settings.\n
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\n \n\n \n \n \n \n \n \n A Systematic Literature Review on RDF Triple Generation From Natural Language Texts.\n \n \n \n \n\n\n \n Regino, A. G.; Rossanez, A.; da Silva Torres, R.; and dos Reis, J. C.\n\n\n \n\n\n\n Semantic Web, 17(1): 31. 2026.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{doi:10.1177/22104968251398355,\n  author = {André Gomes Regino and Anderson Rossanez and Ricardo da Silva Torres and Julio Cesar dos Reis},\n  title = {A Systematic Literature Review on RDF Triple Generation From Natural Language Texts},\n  journal = {Semantic Web},\n  volume = {17},\n  number = {1},\n  pages = {31},\n  year = {2026},\n  doi = {10.1177/22104968251398355},\n  url = {https://doi.org/10.1177/22104968251398355},\n  abstract = {We live in a big data era of unstructured data expressed as natural language (NL) texts. As the volume of text-based information grows, effective methods for encoding and extracting meaningful knowledge from this corpus are of paramount relevance. A challenging task concerns transforming NL texts into structured and semantically rich data. Semantic web technologies have revolutionized how we represent and access structured knowledge. Resource description framework (RDF) triples serve as a fundamental building block for this purpose, enabling the integration of diverse data sources. This investigation examines methods for RDF triple generation and knowledge graphs (KGs) enhancement from NL texts. This study area presents wide-ranging applications encompassing knowledge representation, data integration, NL understanding, and information retrieval. Our systematic literature review addresses the understanding, characterization, and identification of challenges and limitations in existing approaches to RDF triple generation from NL texts and their inclusion into an existing KG. We retrieved, categorized, and analyzed 150 articles from several scientific databases. We provide a comprehensive overview of the field, identify research gaps, and provide directions for future research. We found the most commonly available study categories, especially considering the domain, target language, the public availability of datasets, and real-world applications. Our results reveal a growing trend in this field in the last few years related to the use of transformer-based machine learning methods for triple generation. Our study also drives innovation by highlighting open research questions and providing a road map for future investigations.},\n}\n\n
\n
\n\n\n
\n We live in a big data era of unstructured data expressed as natural language (NL) texts. As the volume of text-based information grows, effective methods for encoding and extracting meaningful knowledge from this corpus are of paramount relevance. A challenging task concerns transforming NL texts into structured and semantically rich data. Semantic web technologies have revolutionized how we represent and access structured knowledge. Resource description framework (RDF) triples serve as a fundamental building block for this purpose, enabling the integration of diverse data sources. This investigation examines methods for RDF triple generation and knowledge graphs (KGs) enhancement from NL texts. This study area presents wide-ranging applications encompassing knowledge representation, data integration, NL understanding, and information retrieval. Our systematic literature review addresses the understanding, characterization, and identification of challenges and limitations in existing approaches to RDF triple generation from NL texts and their inclusion into an existing KG. We retrieved, categorized, and analyzed 150 articles from several scientific databases. We provide a comprehensive overview of the field, identify research gaps, and provide directions for future research. We found the most commonly available study categories, especially considering the domain, target language, the public availability of datasets, and real-world applications. Our results reveal a growing trend in this field in the last few years related to the use of transformer-based machine learning methods for triple generation. Our study also drives innovation by highlighting open research questions and providing a road map for future investigations.\n
\n\n\n
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\n \n\n \n \n \n \n \n \n BENCH4T3: A Framework to Create Benchmarks for Text-to-Triples Alignment Generation.\n \n \n \n \n\n\n \n Chico, V. J. S.; Regino, A. G.; and dos Reis, J. C.\n\n\n \n\n\n\n Journal of the Brazilian Computer Society, 32(1): 85–101. Feb. 2026.\n \n\n\n\n
\n\n\n\n \n \n \"BENCH4T3:Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{Chico_Regino_dos_Reis_2026,\n  title = {BENCH4T3: A Framework to Create Benchmarks for Text-to-Triples Alignment Generation},\n  volume = {32},\n  url = {https://journals-sol.sbc.org.br/index.php/jbcs/article/view/5809},\n  doi = {10.5753/jbcs.2026.5809},\n  abstract = {Integrating Large Language Models (LLMs) with Knowledge Graphs (KGs) can significantly enhance their capabilities, leveraging LLMs’ text generation skills with KGs’ explanatory power. However, establishing this connection is challenging and demands proper alignment between unstructured texts and triples. Building benchmarks demands massive human effort in data curation and translation for non-English languages. The demand for adequate benchmarks for validation purposes negatively impacts research advancements. This study proposes an end-to-end framework to guide the automatic construction of text-to-triple alignment benchmarks for any language, using KGs as input. Our solution extracts relations from input triples and processes them to create accurately mapped texts. The proposed pipeline utilizes data curation through prompt engineering and data augmentation to enhance diversity in the generated examples. We experimentally evaluate our framework for creating a bimodal representation of RDF triples and natural language texts, assessing its ability to generate natural language from these triples. A key focus is on developing a benchmark for the underrepresented Portuguese language, facilitating the construction of models that connect structured data (triples) with text. Our solution is suited to creating a benchmark to improve alignment between KG triples and text data. The results indicate that the generated benchmark outperforms the results of existing solutions. The generative approach benefits from our Portuguese benchmark, achieving competitive results compared to established literature benchmarks. Our solution enables automatic generation of benchmarks for aligning triples and text.},\n  number = {1},\n  journal = {Journal of the Brazilian Computer Society},\n  author = {Chico, Victor Jesus Sotelo and Regino, André Gomes and dos Reis, Julio Cesar},\n  year = {2026},\n  month = {Feb.},\n  pages = {85–101},\n  timestamp = {Sat, 28 Mar 2026 00:00:00 +0100},\n}\n\n
\n
\n\n\n
\n Integrating Large Language Models (LLMs) with Knowledge Graphs (KGs) can significantly enhance their capabilities, leveraging LLMs’ text generation skills with KGs’ explanatory power. However, establishing this connection is challenging and demands proper alignment between unstructured texts and triples. Building benchmarks demands massive human effort in data curation and translation for non-English languages. The demand for adequate benchmarks for validation purposes negatively impacts research advancements. This study proposes an end-to-end framework to guide the automatic construction of text-to-triple alignment benchmarks for any language, using KGs as input. Our solution extracts relations from input triples and processes them to create accurately mapped texts. The proposed pipeline utilizes data curation through prompt engineering and data augmentation to enhance diversity in the generated examples. We experimentally evaluate our framework for creating a bimodal representation of RDF triples and natural language texts, assessing its ability to generate natural language from these triples. A key focus is on developing a benchmark for the underrepresented Portuguese language, facilitating the construction of models that connect structured data (triples) with text. Our solution is suited to creating a benchmark to improve alignment between KG triples and text data. The results indicate that the generated benchmark outperforms the results of existing solutions. The generative approach benefits from our Portuguese benchmark, achieving competitive results compared to established literature benchmarks. Our solution enables automatic generation of benchmarks for aligning triples and text.\n
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\n \n\n \n \n \n \n \n \n Retrieval-Augmented Generation in Healthcare Systems: A Systematic Review with Emphasis on Public Data.\n \n \n \n \n\n\n \n Pereira, R. S. N.; Regino, A. G.; Zagatti, F. R.; de Moraes, M. B.; Ruppert, G.; Monteiro, A. C.; and Bonacin, R.\n\n\n \n\n\n\n In Proceedings of the 26th Brazilian Symposium on Health Informatics (SBCAS'26), pages 918–929, Porto Alegre, RS, Brasil, 2026. SBC\n \n\n\n\n
\n\n\n\n \n \n \"Retrieval-AugmentedPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{pereira2026raghealthcare,\n  author = {Rafael Santos Novo Pereira and André Gomes Regino and Fernando Rezende Zagatti and Matheus Bernardelli de Moraes and Guilherme Ruppert and Ana Carolina Monteiro and Rodrigo Bonacin},\n  title = {Retrieval-Augmented Generation in Healthcare Systems: A Systematic Review with Emphasis on Public Data},\n  booktitle = {Proceedings of the 26th Brazilian Symposium on Health Informatics (SBCAS'26)},\n  location = {Ouro Preto/MG},\n  year = {2026},\n  pages = {918--929},\n  publisher = {SBC},\n  address = {Porto Alegre, RS, Brasil},\n  doi = {10.5753/sbcas.2026.21577},\n  url = {https://sol.sbc.org.br/index.php/sbcas/article/view/42819},\n}\n\n
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\n \n\n \n \n \n \n \n \n Domain-Specific Fine-Tuning of Large Language Models for Pharmacological Question Answering.\n \n \n \n \n\n\n \n Verol, F.; Regino, A. G.; Zagatti, F. R.; de Franco Rosa, F.; dos Reis, J. C.; and Bonacin, R.\n\n\n \n\n\n\n In Proceedings of the 26th Brazilian Symposium on Health Informatics (SBCAS'26), pages 870–881, Porto Alegre, RS, Brasil, 2026. SBC\n \n\n\n\n
\n\n\n\n \n \n \"Domain-SpecificPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{verol2026pharmacological,\n  author = {Felipe Verol and André Gomes Regino and Fernando Rezende Zagatti and Ferrucio de Franco Rosa and Julio Cesar dos Reis and Rodrigo Bonacin},\n  title = {Domain-Specific Fine-Tuning of Large Language Models for Pharmacological Question Answering},\n  booktitle = {Proceedings of the 26th Brazilian Symposium on Health Informatics (SBCAS'26)},\n  location = {Ouro Preto/MG},\n  year = {2026},\n  pages = {870--881},\n  publisher = {SBC},\n  address = {Porto Alegre, RS, Brasil},\n  doi = {10.5753/sbcas.2026.21567},\n  url = {https://sol.sbc.org.br/index.php/sbcas/article/view/42815},\n}\n\n
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\n \n\n \n \n \n \n \n \n ELSA-Compliant Explainable Recommender Systems.\n \n \n \n \n\n\n \n Kalidas, V.; Rossanez, A.; Regino, A.; dos Reis, J.; and Torres, R.\n\n\n \n\n\n\n ACM Trans. Recomm. Syst., 5(1). sep 2026.\n \n\n\n\n
\n\n\n\n \n \n \"ELSA-CompliantPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@article{10.1145/3797875,\n  author = {Kalidas, Varsha and Rossanez, Anderson and Regino, Andre and dos Reis, Julio and Torres, Ricardo},\n  title = {ELSA-Compliant Explainable Recommender Systems},\n  year = {2026},\n  issue_date = {January 2027},\n  publisher = {Association for Computing Machinery},\n  address = {New York, NY, USA},\n  volume = {5},\n  number = {1},\n  url = {https://doi.org/10.1145/3797875},\n  doi = {10.1145/3797875},\n  abstract = {Recommender systems are among the most popular artificial intelligence applications. Ensuring that recommendations not only support improving business-oriented performance indicators but also comply with existing domain-specific Ethical, Legal, and Societal Aspects (ELSA) is paramount. This article introduces an ELSA-compliant Explainable Recommender System, an architecture for implementing ELSA-compliant recommendations. Our proposed solution assumes that information regarding items, users, their interactions, and ELSA is encoded in Knowledge Graphs (KG). Given recommendations provided by a base off-the-shelf KG-based recommendation system, our system re-ranks and filters out recommendable items based on their ELSA-compliance, encoded in pre-defined domain-specific ELSA constraints. Our approach includes an explainer that leverages Large Language Models to provide explanations of the adequacy of recommended items based on ELSA. The proposed components have been assessed in the movie and animal treatment recommendation tasks. Experimental results suggest that the proposed solution effectively ensures ELSA-compliant recommendations with adequate humanized explanations in natural language to the end user.},\n  journal = {ACM Trans. Recomm. Syst.},\n  month = {sep},\n  articleno = {6},\n  numpages = {40},\n  keywords = {Ethical, legal, and societal aspects (ELSA), recommendation, re-ranking, filtering, large language model, explainability},\n}\n\n
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\n\n\n
\n Recommender systems are among the most popular artificial intelligence applications. Ensuring that recommendations not only support improving business-oriented performance indicators but also comply with existing domain-specific Ethical, Legal, and Societal Aspects (ELSA) is paramount. This article introduces an ELSA-compliant Explainable Recommender System, an architecture for implementing ELSA-compliant recommendations. Our proposed solution assumes that information regarding items, users, their interactions, and ELSA is encoded in Knowledge Graphs (KG). Given recommendations provided by a base off-the-shelf KG-based recommendation system, our system re-ranks and filters out recommendable items based on their ELSA-compliance, encoded in pre-defined domain-specific ELSA constraints. Our approach includes an explainer that leverages Large Language Models to provide explanations of the adequacy of recommended items based on ELSA. The proposed components have been assessed in the movie and animal treatment recommendation tasks. Experimental results suggest that the proposed solution effectively ensures ELSA-compliant recommendations with adequate humanized explanations in natural language to the end user.\n
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\n \n\n \n \n \n \n \n \n Model interpretation using improved local regression with variable importance.\n \n \n \n \n\n\n \n Shimizu, G. Y.; Izbicki, R.; Zagatti, F. R.; Lopes, F. L.; Regino, A. G.; Bonacin, R.; and Carvalho, A. C. P. L. F. d.\n\n\n \n\n\n\n Journal of the Brazilian Computer Society, 32(1): 2274–2292. Sep. 2026.\n \n\n\n\n
\n\n\n\n \n \n \"ModelPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{Shimizu_Izbicki_Zagatti_Lopes_Regino_Bonacin_Carvalho_2026,\n  title = {Model interpretation using improved local regression with variable importance},\n  volume = {32},\n  url = {https://journals-sol.sbc.org.br/index.php/jbcs/article/view/6073},\n  doi = {10.5753/jbcs.2026.6073},\n  abstractnote = {One of the main limitations for the trust in the use of machine learning models is the understanding of how they produce their predictions. This limitation is related to an increasing demand for transparency in decision-making. Interpretability refers to how well a user can understand the models decision-making process without necessarily knowing its internal mechanisms. Several interpretability methods have emerged in the last years, such as LIME and Shapley values, which are valued for their flexibility, intuitive appeal, and strong theoretical foundations. While these methods have significantly contributed to better model transparency, they face challenges in several model deployment scenarios, such as handling irrelevant features or maintaining stability under small data perturbations. This article introduces two new agnostic interpretability methods, namely VarImp and SupClus, which overcome these issues by using local regressions fits with a weighted distance that takes into account variable importance. Whereas VarImp generates interpretations for each instance and can be applied to datasets with more complex relationships, SupClus interprets data clusters of instances with similar interpretations and can be applied to simpler datasets where data clusters can be found. In this paper, we compare these proposed methods with state-of-the-art methods and show that the proposed methods generate either equal or better interpretations, according to several proposed quantitative metrics (mean square error of coefficients, effect correlation, prediction correlation and ICE effect correlation), particularly in high-dimensional problems with irrelevant features and when the relationship between features and target is non-linear.},\n  number = {1},\n  journal = {Journal of the Brazilian Computer Society},\n  author = {Shimizu, Gilson Yuuji and Izbicki, Rafael and Zagatti, Fernando Rezende and Lopes, Filipe Loyola and Regino, André Gomes and Bonacin, Rodrigo and Carvalho, Andre C. P. L. F. de},\n  year = {2026},\n  month = {Sep.},\n  pages = {2274–2292},\n}\n\n
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\n \n\n \n \n \n \n \n NORKE: A Framework for Normative Rule-Centric Knowledge Graph Construction using Language Models.\n \n \n \n\n\n \n Souza, E.; Regino, A. G.; and Reis, J. C. d.\n\n\n \n\n\n\n In Proceedings of the 7th International Workshop on Knowledge Graph Construction (KGCW 2026) co-located with the Extended Semantic Web Conference 2026 (ESWC 2026), volume 4245, pages 96–111, Dubrovnik, Croatia, 2026. \n 7th International Workshop on Knowledge Graph Construction (KGCW 2026)\n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{souza2026norke,\n  author    = {Souza, E. and Regino, André Gomes and Reis, Julio Cesar dos},\n  title     = {NORKE: A Framework for Normative Rule-Centric Knowledge Graph Construction using Language Models},\n  booktitle = {Proceedings of the 7th International Workshop on Knowledge Graph Construction (KGCW 2026) co-located with the Extended Semantic Web Conference 2026 (ESWC 2026)},\n  year      = {2026},\n  volume    = {4245},\n  pages     = {96--111},\n  address   = {Dubrovnik, Croatia},\n  note      = {7th International Workshop on Knowledge Graph Construction (KGCW 2026)}\n}
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\n  \n 2025\n \n \n (11)\n \n \n
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\n \n\n \n \n \n \n \n \n Can LLMs be Knowledge Graph Curators for Validating Triple Insertions?.\n \n \n \n \n\n\n \n Regino, A.; and dos Reis, J. C.\n\n\n \n\n\n\n In Genet Asefa Gesese, H. S.; and Chen, L., editor(s), Proceedings of the 31st International Conference on Computational Linguistics, COLING 2025 - Workshops, Abu Dhabi, UAE, January 19-24, 2025, pages 87–99, Abu Dhabi, UAE, 2025. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n \"CanPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 4 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{regino-dos-reis-2025-llms,\n  title = {Can LLMs be Knowledge Graph Curators for Validating Triple Insertions?},\n  author = {André Regino and Julio Cesar dos Reis},\n  editor = {Genet Asefa Gesese, Harald Sack, Heiko Paulheim, Albert Merono-Penuela and Lihu Chen},\n  booktitle = {Proceedings of the 31st International Conference on Computational Linguistics, {COLING} 2025 - Workshops, Abu Dhabi, UAE, January 19-24, 2025},\n  year = {2025},\n  address = {Abu Dhabi, UAE},\n  publisher = {Association for Computational Linguistics},\n  url = {https://aclanthology.org/2025.genaik-1.10/},\n  pages = {87--99},\n  timestamp = {Thu, 31 Jul 2025 01:00:00 +0200},\n  biburl = {https://dblp.org/rec/conf/coling/ReginoR25.bib},\n}\n\n
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\n \n\n \n \n \n \n \n UpKG: A Framework for Integrating and Evaluating Novel Domains into Knowledge Graphs.\n \n \n \n\n\n \n Zevallos-Quispe, J. M.; Regino, A. G.; Chico, V. J. S.; de Freitas, V. H.; and dos Reis, J. C.\n\n\n \n\n\n\n In Coenen, F.; Fred, A.; Aveiro, D.; Dietz, J.; Poggi, A.; Gruenwald, L.; Masciari, E.; and Bernardino, J., editor(s), Knowledge Discovery, Knowledge Engineering and Knowledge Management, pages 203–231, Cham, 2025. Springer Nature Switzerland\n \n\n\n\n
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@inproceedings{10.1007/978-3-031-87569-4_10,\n  author = {Zevallos-Quispe, Jesamin Melissa and Regino, André Gomes and Chico, Victor Jesús Sotelo and de Freitas, Victor Hochgreb and dos Reis, Julio Cesar},\n  editor = {Coenen, Frans and Fred, Ana and Aveiro, David and Dietz, Jan and Poggi, Antonella and Gruenwald, Le and Masciari, Elio and Bernardino, Jorge},\n  title = {UpKG: A Framework for Integrating and Evaluating Novel Domains into Knowledge Graphs},\n  booktitle = {Knowledge Discovery, Knowledge Engineering and Knowledge Management},\n  year = {2025},\n  publisher = {Springer Nature Switzerland},\n  address = {Cham},\n  pages = {203--231},\n  isbn = {978-3-031-87569-4},\n  doi = {https://doi.org/10.1007/978-3-031-87569-4_10},\n}\n\n
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\n \n\n \n \n \n \n \n \n ELSA Knowledge Graphs for Animal Treatment Recommendations.\n \n \n \n \n\n\n \n Kalidas, V.; Regino, A. G.; Rossanez, A.; dos Reis, J. C.; Alskaif, T.; and Torres, R. S.\n\n\n \n\n\n\n In Proceedings of the 2nd International Workshop on Knowledge Graphs for Responsible AI (KG-STAR 2025) co-located with the 22nd Extended Semantic Web Conference (ESWC 2025), Portorož, Slovenia, June 2nd, 2025, volume 4018, of CEUR Workshop Proceedings, pages 12–30, 2025. CEUR-WS.org\n \n\n\n\n
\n\n\n\n \n \n \"ELSAPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{regino2025elsa,\n  title = {ELSA Knowledge Graphs for Animal Treatment Recommendations},\n  author = {Kalidas, V. and Regino, A. G. and Rossanez, A. and dos Reis, J. C. and Alskaif, T. and Torres, R. S.},\n  year = {2025},\n  series = {{CEUR} Workshop Proceedings},\n  volume = {4018},\n  pages = {12--30},\n  publisher = {CEUR-WS.org},\n  booktitle = {Proceedings of the 2nd International Workshop on Knowledge Graphs for Responsible AI (KG-STAR 2025) co-located with the 22nd Extended Semantic Web Conference (ESWC 2025), Portorož, Slovenia, June 2nd, 2025},\n  timestamp = {Wed, 06 May 2026 01:00:00 +0200},\n  url = {https://ceur-ws.org/Vol-4018/paper1.pdf},\n}\n\n
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\n \n\n \n \n \n \n \n \n StudYard: Aprimorando o Engajamento e a Autonomia do Estudante apoiado por IA Generativa.\n \n \n \n \n\n\n \n Oliveira, H.; Oliveira, G.; Viriato, P.; Silva, E.; Regino, A. G.; and Reis, J.\n\n\n \n\n\n\n In Anais Estendidos do XIV Congresso Brasileiro de Informática na Educação (CBIE'25), pages 212–215, Porto Alegre, RS, Brasil, 2025. SBC\n \n\n\n\n
\n\n\n\n \n \n \"StudYard:Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{cbie,\n  author = {Henrique Oliveira and Gabriel Oliveira and Paula Viriato and Eryck Silva and André Gomes Regino and Julio Reis},\n  title = {StudYard: Aprimorando o Engajamento e a Autonomia do Estudante apoiado por IA Generativa},\n  booktitle = {Anais Estendidos do XIV Congresso Brasileiro de Informática na Educação (CBIE'25)},\n  location = {Curitiba/PR},\n  year = {2025},\n  issn = {0000-0000},\n  pages = {212--215},\n  publisher = {SBC},\n  address = {Porto Alegre, RS, Brasil},\n  doi = {10.5753/cbie_estendido.2025.13702},\n  url = {https://sol.sbc.org.br/index.php/cbie_estendido/article/view/38922},\n}\n\n
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\n \n\n \n \n \n \n \n \n LLM-Based Automatic Generation of Multiple-Choice Questions With Meaningful Distractors.\n \n \n \n \n\n\n \n Chico, V.; Regino, A. G.; Bonacin, R.; and Reis, J.\n\n\n \n\n\n\n In Anais do XXXVI Simpósio Brasileiro de Informática na Educação (SBIE'25), pages 813–827, Porto Alegre, RS, Brasil, 2025. SBC\n \n\n\n\n
\n\n\n\n \n \n \"LLM-BasedPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{sbie,\n  author = {Víctor Chico and André Gomes Regino and Rodrigo Bonacin and Julio Reis},\n  title = {LLM-Based Automatic Generation of Multiple-Choice Questions With Meaningful Distractors},\n  booktitle = {Anais do XXXVI Simpósio Brasileiro de Informática na Educação (SBIE'25)},\n  location = {Curitiba/PR},\n  year = {2025},\n  issn = {0000-0000},\n  pages = {813--827},\n  publisher = {SBC},\n  address = {Porto Alegre, RS, Brasil},\n  doi = {10.5753/sbie.2025.12675},\n  url = {https://sol.sbc.org.br/index.php/sbie/article/view/38469},\n}\n\n
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\n \n\n \n \n \n \n \n \n Leveraging Large Language Models for Semantic Evaluation of RDF Triples.\n \n \n \n \n\n\n \n Regino, A. G.; Zagatti, F. R.; Bonacin, R.; Chico, V. J. S.; Hochgreb, V.; and dos Reis, J. C.\n\n\n \n\n\n\n In Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD and KMIS, pages 74–85, 2025. SCITEPRESS\n \n\n\n\n
\n\n\n\n \n \n \"LeveragingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{regino_llm_semantic_evaluation,\n  author = {Andr{\\'{e}} Gomes Regino and Fernando Rodrigues Zagatti and Rafael Bonacin and V{\\'{i}}tor Jos{\\'{e}} Sanches Chico and Victor Hochgreb and J{\\'{u}}lio Cesar dos Reis},\n  title = {Leveraging Large Language Models for Semantic Evaluation of {RDF} Triples},\n  booktitle = {Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: {KEOD} and {KMIS}},\n  pages = {74--85},\n  publisher = {{SCITEPRESS}},\n  year = {2025},\n  isbn = {978-989-758-769-6},\n  issn = {2184-3228},\n  doi = {10.5220/0013837600004000},\n  url = {https://doi.org/10.5220/0013837600004000},\n  timestamp = {Thu, 20 Nov 2025 00:00:00 +0100},\n}\n\n
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\n \n\n \n \n \n \n \n \n Suggesting Product Prices in Automotive E-Commerce: A Study Assessing Regression Models and Explicability.\n \n \n \n \n\n\n \n Regino, A. G.; Shimizu, G. Y.; Zagatti, F. R.; Lopes, F.; Bonacin, R.; dos Reis, J. C.; and de Aguiar, C. D.\n\n\n \n\n\n\n In Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, pages 147–158, 2025. SCITEPRESS\n \n\n\n\n
\n\n\n\n \n \n \"SuggestingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{regino_pricing_autoparts,\n  author = {Andr{\\'{e}} Gomes Regino and Gabriel Yukio Shimizu and Fernando Rodrigues Zagatti and Felipe Lopes and Rafael Bonacin and J{\\'{u}}lio Cesar dos Reis and Cl{\\'{a}}udio Dutra de Aguiar},\n  title = {Suggesting Product Prices in Automotive E-Commerce: A Study Assessing Regression Models and Explicability},\n  booktitle = {Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: {KDIR}},\n  pages = {147--158},\n  publisher = {{SCITEPRESS}},\n  year = {2025},\n  isbn = {978-989-758-769-6},\n  issn = {2184-3228},\n  doi = {10.5220/0013830400004000},\n  url = {https://doi.org/10.5220/0013830400004000},\n  timestamp = {Thu, 25 Dec 2025 00:00:00 +0100},\n}\n\n
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\n \n\n \n \n \n \n \n \n Multi-Agent LLM Approach for Moderating E-Commerce Customer Service Responses.\n \n \n \n \n\n\n \n Gomes, T.; Regino, A.; Caus, R.; Sotelo, V.; and Reis, J.\n\n\n \n\n\n\n In Proceedings of the 31st Brazilian Symposium on Multimedia and the Web (WebMedia'25), pages 349–357, Porto Alegre, RS, Brasil, 2025. SBC\n \n\n\n\n
\n\n\n\n \n \n \"Multi-AgentPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{webmedia,\n  author = {Tiago Gomes and André Regino and Rodrigo Caus and Victor Sotelo and Julio Reis},\n  title = {Multi-Agent LLM Approach for Moderating E-Commerce Customer Service Responses},\n  booktitle = {Proceedings of the 31st Brazilian Symposium on Multimedia and the Web (WebMedia'25)},\n  location = {Rio de Janeiro/RJ},\n  year = {2025},\n  pages = {349--357},\n  publisher = {SBC},\n  address = {Porto Alegre, RS, Brasil},\n  doi = {10.5753/webmedia.2025.16162},\n  url = {https://sol.sbc.org.br/index.php/webmedia/article/view/37979},\n}\n\n
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\n \n\n \n \n \n \n \n Ajuste Fino de Grandes Modelos de Linguagem para Análise de Propriedades Textuais no DrugBank.\n \n \n \n\n\n \n Verol, F. R.; Regino, A. G.; and Bonacin, R.\n\n\n \n\n\n\n In Anais da XXVII Jornada de Iniciação Científica do CTI Renato Archer (JICC 2025), Campinas, Brasil, 2025. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{verol_finetuning_drugbank,\n  author = {Felipe Rodrigues Verol and Andr{\\'{e}} Gomes Regino and Rodrigo Bonacin},\n  title = {Ajuste Fino de Grandes Modelos de Linguagem para An{\\'{a}}lise de Propriedades Textuais no {DrugBank}},\n  booktitle = {Anais da {XXVII} Jornada de Inicia{\\c{c}}{\\~{a}}o Cient{\\'{\\i}}fica do {CTI} Renato Archer ({JICC} 2025)},\n  year = {2025},\n  address = {Campinas, Brasil},\n}\n\n
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\n \n\n \n \n \n \n \n \n Enhancing Knowledge Graphs with Large Language Models: Contributions to E-commerce Question Answering Systems.\n \n \n \n \n\n\n \n Regino, A.; and Reis, J.\n\n\n \n\n\n\n In Anais Estendidos do XXXI Simpósio Brasileiro de Sistemas Multimídia e Web (WebMedia'25), pages 21–22, Porto Alegre, RS, Brasil, 2025. SBC\n \n\n\n\n
\n\n\n\n \n \n \"EnhancingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{webmedia_estendido,\n  author = {André Regino and Julio Reis},\n  title = {Enhancing Knowledge Graphs with Large Language Models: Contributions to E-commerce Question Answering Systems},\n  booktitle = {Anais Estendidos do XXXI Simpósio Brasileiro de Sistemas Multimídia e Web (WebMedia'25)},\n  location = {Rio de Janeiro/RJ},\n  year = {2025},\n  issn = {2596-1683},\n  pages = {21--22},\n  publisher = {SBC},\n  address = {Porto Alegre, RS, Brasil},\n  doi = {10.5753/webmedia_estendido.2025.16346},\n  url = {https://sol.sbc.org.br/index.php/webmedia_estendido/article/view/38152},\n}\n\n
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\n \n\n \n \n \n \n \n \n KG-Quizzer: Prompt Refinement via Knowledge Graphs for the Automatic Generation of Questionnaires in Portuguese.\n \n \n \n \n\n\n \n Medeiros, D.; Leite, G.; Regino, A. G.; Chico, V. J. S.; Rosa, F. d. F.; and Reis, J. C. d.\n\n\n \n\n\n\n In Proceedings of the 18th Seminar on Ontology Research in Brazil (ONTOBRAS 2025) and 9th Doctoral and Masters Consortium on Ontologies (WTDO 2025), volume 4177, of CEUR Workshop Proceedings, pages 38–50, São José dos Campos, Brazil, 2025. CEUR-WS.org\n \n\n\n\n
\n\n\n\n \n \n \"KG-Quizzer:Paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{medeiros2025kgquizzer,\n  title = {KG-Quizzer: Prompt Refinement via Knowledge Graphs for the Automatic Generation of Questionnaires in Portuguese},\n  author = {Medeiros, Davisson and Leite, Gabriel and Regino, André Gomes and Chico, Victor Jesus Soleto and Rosa, Ferrucio de Franco and Reis, Julio Cesar dos},\n  booktitle = {Proceedings of the 18th Seminar on Ontology Research in Brazil (ONTOBRAS 2025) and 9th Doctoral and Masters Consortium on Ontologies (WTDO 2025)},\n  year = {2025},\n  pages = {38--50},\n  volume = {4177},\n  series = {CEUR Workshop Proceedings},\n  publisher = {CEUR-WS.org},\n  address = {São José dos Campos, Brazil},\n  url = {https://ceur-ws.org/Vol-4177/},\n  timestamp = {Mon, 20 Apr 2026 01:00:00 +0200},\n}\n\n
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\n  \n 2024\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n \n Generating E-commerce Related Knowledge Graph from Text: Open Challenges and Early Results using LLMs.\n \n \n \n \n\n\n \n Regino, A. G.; and dos Reis, J. C.\n\n\n \n\n\n\n In Sanju Tiwari, N. M.; and Kejriwal, M., editor(s), Proceedings of the 3rd International workshop one knowledge graph generation from text (Text2KG) co-located with the 21st Extended Semantic Web Conference (ESWC), Hersonissos, Greece, May 26-30, 2024, volume 3747, of CEUR Workshop Proceedings, pages 21–39, 2024. CEUR-WS.org\n \n\n\n\n
\n\n\n\n \n \n \"GeneratingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{regino2024generating,\n  title = {Generating E-commerce Related Knowledge Graph from Text: Open Challenges and Early Results using LLMs},\n  author = {Regino, Andr{\\'e} Gomes and dos Reis, Julio Cesar},\n  year = {2024},\n  editor = {Sanju Tiwari, Nandana Mihindukulasooriya, Francesco Osborne, Dimitris Kontokostas, Jennifer D Souza and Mayank Kejriwal},\n  series = {{CEUR} Workshop Proceedings},\n  volume = {3747},\n  pages = {21--39},\n  publisher = {CEUR-WS.org},\n  booktitle = {Proceedings of the 3rd International workshop one knowledge graph generation from text (Text2KG) co-located with the 21st Extended Semantic Web Conference (ESWC), Hersonissos, Greece, May 26-30, 2024},\n  timestamp = {Thu, 31 Oct 2024 00:00:00 +0100},\n  url = {https://ceur-ws.org/Vol-3747/text2kg\\_paper11.pdf},\n}\n\n
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\n \n\n \n \n \n \n \n \n Humanizing Answers for Compatibility Questions in E-commerce using Large Language Models.\n \n \n \n \n\n\n \n Regino, A.; Hochgreb, V.; and dos Reis, J. C.\n\n\n \n\n\n\n In Anais do XXXIX Simpósio Brasileiro de Bancos de Dados, pages 300–312, 2024. SBC\n \n\n\n\n
\n\n\n\n \n \n \"HumanizingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{sbbd_humanizing,\n  author = {André Regino and Victor Hochgreb and Julio Cesar dos Reis},\n  title = {Humanizing Answers for Compatibility Questions in E-commerce using Large Language Models},\n  booktitle = {Anais do XXXIX Simpósio Brasileiro de Bancos de Dados},\n  location = {Florianópolis/SC},\n  year = {2024},\n  issn = {2763-8979},\n  pages = {300--312},\n  publisher = {SBC},\n  doi = {10.5753/sbbd.2024.240657},\n  url = {https://doi.org/10.5753/sbbd.2024.240657},\n  timestamp = {Tue, 05 Aug 2025 01:00:00 +0200},\n}\n\n
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\n \n\n \n \n \n \n \n \n Semantic Structuring of E-commerce Texts: The QART Framework.\n \n \n \n \n\n\n \n Regino, A.; and dos Reis, J. C.\n\n\n \n\n\n\n In Anais Estendidos do XXXIX Simpósio Brasileiro de Bancos de Dados, pages 144–150, 2024. SBC\n \n\n\n\n
\n\n\n\n \n \n \"SemanticPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{sbbd_wtdbd,\n  author = {André Regino and Julio Cesar dos Reis},\n  title = {Semantic Structuring of E-commerce Texts: The QART Framework},\n  booktitle = {Anais Estendidos do XXXIX Simpósio Brasileiro de Bancos de Dados},\n  location = {Florianópolis/SC},\n  year = {2024},\n  issn = {0000-0000},\n  pages = {144--150},\n  publisher = {SBC},\n  doi = {10.5753/sbbd_estendido.2024.243761},\n  url = {https://sol.sbc.org.br/index.php/sbbd_estendido/article/view/30785},\n}\n\n
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\n  \n 2023\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n Leveraging Knowledge Graphs for E-commerce Product Recommendations.\n \n \n \n\n\n \n Regino, A. G.; Caus, R. O.; Hochgreb, V.; and Reis, J. C. d.\n\n\n \n\n\n\n Springer Nature Computer Science, 4(5): 689. Sep 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{regino_recommendation_journal_2023,\n  author = {Regino, Andr{\\'e} Gomes and Caus, Rodrigo Oliveira and Hochgreb, Victor and Reis, Julio Cesar dos},\n  title = {Leveraging Knowledge Graphs for E-commerce Product Recommendations},\n  journal = {Springer Nature Computer Science},\n  year = {2023},\n  month = {Sep},\n  day = {08},\n  volume = {4},\n  number = {5},\n  pages = {689},\n  issn = {2661-8907},\n  doi = {10.1007/s42979-023-02149-6},\n  timestamp = {Sat, 30 Sep 2023 01:00:00 +0200},\n}\n\n
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\n \n\n \n \n \n \n \n UpKG: A Framework to Insert New Domains in Knowledge Graphs.\n \n \n \n\n\n \n Zevallos-Quispe, J.; Regino, A. G.; Chico, V. J. S.; Hochgreb, V.; and dos Reis, J. C.\n\n\n \n\n\n\n In Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KEOD, pages 85-95, 2023. INSTICC, SciTePress\n \n\n\n\n
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@inproceedings{keod23,\n  author = {Zevallos{-}Quispe, Jesamin and Regino, André Gomes and Chico, Víctor Jesús Sotelo and Hochgreb, Víctor and dos Reis, Julio Cesar},\n  title = {UpKG: A Framework to Insert New Domains in Knowledge Graphs},\n  booktitle = {Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KEOD},\n  year = {2023},\n  pages = {85-95},\n  publisher = {SciTePress},\n  organization = {INSTICC},\n  doi = {10.5220/0012237600003598},\n  isbn = {978-989-758-671-2},\n  issn = {2184-3228},\n  timestamp = {Sun, 06 Oct 2024 01:00:00 +0200},\n}\n\n
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\n  \n 2022\n \n \n (4)\n \n \n
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\n \n\n \n \n \n \n \n Leveraging Linked Open Data: A Link Maintenance Framework.\n \n \n \n\n\n \n Regino, A. G.; and dos Reis, J. C.\n\n\n \n\n\n\n In Anais Estendidos do XXVIII Simpósio Brasileiro de Sistemas Multimı́dia e Web, pages 15–18, 2022. SBC, SBC\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{regino2022leveraging,\n  title = {Leveraging Linked Open Data: A Link Maintenance Framework},\n  author = {Regino, Andr{\\'e} Gomes and dos Reis, Julio Cesar},\n  booktitle = {Anais Estendidos do XXVIII Simp{\\'o}sio Brasileiro de Sistemas Multim{\\'\\i}dia e Web},\n  pages = {15--18},\n  year = {2022},\n  location = {Curitiba},\n  issn = {2596-1683},\n  doi = {10.5753/webmedia_estendido.2022.225651},\n  organization = {SBC},\n  publisher = {SBC},\n}\n\n
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\n \n\n \n \n \n \n \n \n QART: A Framework to Transform Natural Language Questions and Answers into RDF Triples.\n \n \n \n \n\n\n \n Regino, A. G.; Caus, R. O.; Hochgreb, V.; and dos Reis, J. C.\n\n\n \n\n\n\n In Aveiro, D.; Dietz, J. L. G.; and Filipe, J., editor(s), Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2022, Volume 2: KEOD, Valletta, Malta, October 24-26, 2022, pages 55–65, 2022. SCITEPRESS\n \n\n\n\n
\n\n\n\n \n \n \"QART:Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{regino_qart,\n  author = {Andr{\\'{e}} Gomes Regino and Rodrigo Oliveira Caus and Victor Hochgreb and J{\\'{u}}lio Cesar dos Reis},\n  editor = {David Aveiro and Jan L. G. Dietz and Joaquim Filipe},\n  title = {{QART:} {A} Framework to Transform Natural Language Questions and Answers into {RDF} Triples},\n  booktitle = {Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, {IC3K} 2022, Volume 2: KEOD, Valletta, Malta, October 24-26, 2022},\n  pages = {55--65},\n  publisher = {{SCITEPRESS}},\n  year = {2022},\n  url = {https://doi.org/10.5220/0011529200003335},\n  doi = {10.5220/0011529200003335},\n  timestamp = {Sat, 31 May 2025 01:00:00 +0200},\n}\n\n
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\n \n\n \n \n \n \n \n \n Knowledge Graph-based Product Recommendations on e-Commerce Platforms.\n \n \n \n \n\n\n \n Regino, A. G.; Caus, R. O.; Hochgreb, V.; and dos Reis, J. C.\n\n\n \n\n\n\n In Aveiro, D.; Dietz, J. L. G.; and Filipe, J., editor(s), Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2022, Volume 2: KEOD, Valletta, Malta, October 24-26, 2022, pages 32–42, 2022. SCITEPRESS. Best Student Paper Award\n \n\n\n\n
\n\n\n\n \n \n \"KnowledgePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{regino_recommendation_,\n  author = {Andr{\\'{e}} Gomes Regino and Rodrigo Oliveira Caus and Victor Hochgreb and J{\\'{u}}lio Cesar dos Reis},\n  editor = {David Aveiro and Jan L. G. Dietz and Joaquim Filipe},\n  title = {Knowledge Graph-based Product Recommendations on e-Commerce Platforms},\n  booktitle = {Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, {IC3K} 2022, Volume 2: KEOD, Valletta, Malta, October 24-26, 2022},\n  pages = {32--42},\n  publisher = {SCITEPRESS. Best Student Paper Award},\n  year = {2022},\n  url = {https://doi.org/10.5220/0011388300003335},\n  doi = {10.5220/0011388300003335},\n  timestamp = {Sat, 31 May 2025 01:00:00 +0200},\n}\n\n
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\n \n\n \n \n \n \n \n From Natural Language Texts to RDF Triples: A Novel Approach to Generating e-Commerce Knowledge Graphs.\n \n \n \n\n\n \n Regino, A. G.; Caus, R. O.; Hochgreb, V.; and dos Reis, J. C.\n\n\n \n\n\n\n In Coenen, F.; Fred, A.; Aveiro, D.; Dietz, J.; Bernardino, J.; Masciari, E.; and Filipe, J., editor(s), Knowledge Discovery, Knowledge Engineering and Knowledge Management, volume 1842, of Communications in Computer and Information Science, pages 149–174, 2022. Springer\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{regino_qart_book_chapter_2023,\n  author = {Regino, Andr{\\'e} Gomes and Caus, Rodrigo Oliveira and Hochgreb, Victor and dos Reis, Julio Cesar},\n  editor = {Coenen, Frans and Fred, Ana and Aveiro, David and Dietz, Jan and Bernardino, Jorge and Masciari, Elio and Filipe, Joaquim},\n  title = {From Natural Language Texts to RDF Triples: A Novel Approach to Generating e-Commerce Knowledge Graphs},\n  booktitle = {Knowledge Discovery, Knowledge Engineering and Knowledge Management},\n  year = {2022},\n  publisher = {Springer},\n  pages = {149--174},\n  isbn = {978-3-031-43471-6},\n  doi = {10.1007/978-3-031-43471-6_7},\n  timestamp = {Sat, 31 May 2025 01:00:00 +0200},\n  biburl = {https://dblp.org/rec/conf/ic3k/ReginoCHR22b.bib},\n  bibsource = {dblp computer science bibliography, https://dblp.org},\n  series = {Communications in Computer and Information Science},\n  volume = {1842},\n}\n\n
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\n  \n 2021\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n \n UpLOD: A Tool for Inconsistent Links Repairment in the LOD.\n \n \n \n \n\n\n \n Regino, A. G.; Monteiro, E. d. J. P.; dos Santos, A. C.; and dos Reis, J. C.\n\n\n \n\n\n\n In Proceedings of the 7th Workshop on Managing the Evolution and Preservation of the Data Web (MEPDaW) co-located with the 20th International Semantic Web Conference (ISWC 2021), volume 3225, of CEUR Workshop Proceedings, pages 37–41, 2021. CEUR-WS.org\n \n\n\n\n
\n\n\n\n \n \n \"UpLOD:Paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{regino2021uplod,\n  title = {UpLOD: A Tool for Inconsistent Links Repairment in the LOD},\n  author = {Regino, Andr{\\'e} Gomes and Monteiro, Enio de Jesus Pontes and dos Santos, Andressa Cristina and dos Reis, Julio Cesar},\n  pages = {37--41},\n  year = {2021},\n  booktitle = {Proceedings of the 7th Workshop on Managing the Evolution and Preservation of the Data Web (MEPDaW) co-located with the 20th International Semantic Web Conference (ISWC 2021)},\n  series = {{CEUR} Workshop Proceedings},\n  volume = {3225},\n  publisher = {CEUR-WS.org},\n  timestamp = {Fri, 10 Mar 2023 00:00:00 +0100},\n  biburl = {https://dblp.org/rec/conf/semweb/ReginoMSR21.bib},\n  bibsource = {dblp computer science bibliography, https://dblp.org},\n  url = {https://ceur-ws.org/Vol-3225/paper6.pdf},\n}\n\n
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\n \n\n \n \n \n \n \n Link maintenance for integrity in linked open data evolution: Literature survey and open challenges.\n \n \n \n\n\n \n Regino, A. G.; dos Reis, J. C.; Bonacin, R.; Morshed, A.; and Sellis, T.\n\n\n \n\n\n\n Semantic Web, 12(3): 517–541. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{reginolink,\n  title = {Link maintenance for integrity in linked open data evolution: Literature survey and open challenges},\n  author = {Regino, Andre Gomes and dos Reis, Julio Cesar and Bonacin, Rodrigo and Morshed, Ahsan and Sellis, Timos},\n  journal = {Semantic Web},\n  volume = {12},\n  number = {3},\n  pages = {517--541},\n  year = {2021},\n  doi = {10.3233/SW-200398},\n  timestamp = {Mon, 28 Aug 2023 01:00:00 +0200},\n}\n\n
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\n  \n 2020\n \n \n (4)\n \n \n
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\n \n\n \n \n \n \n \n \n Análise Experimental da Evolução de Links em Dados Interconectados Abertos.\n \n \n \n \n\n\n \n Matsoui, J. K. R.; Regino, A. G.; and dos Reis, J. C.\n\n\n \n\n\n\n Technical Report Technical report, Universidade Estadual de Campinas, 2020.\n \n\n\n\n
\n\n\n\n \n \n \"AnálisePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@techreport{2020matsoui,\n  title = {Análise Experimental da Evolução de Links em Dados Interconectados Abertos},\n  author = {Matsoui, Julio Kiyoshi Rodrigues and Regino, André Gomes and dos Reis, Julio Cesar},\n  year = {2020},\n  institution = {Technical report, Universidade Estadual de Campinas},\n  url = {https://www.ic.unicamp.br/~reltech/2020/20-06.pdf},\n}\n\n
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\n \n\n \n \n \n \n \n \n Discovering Semantically Broken Links in LOD Datasets.\n \n \n \n \n\n\n \n Regino, A. G.; and dos Reis, J. C.\n\n\n \n\n\n\n In Workshop Managing the Evolution and Preservation of the Data Web (MEPDaW'20) co-located at the 19th International Semantic Web Conference (ISWC’20), virtual conference., volume 2821, of CEUR Workshop Proceedings, pages 17–26, 2020. CEUR-WS.org\n \n\n\n\n
\n\n\n\n \n \n \"DiscoveringPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{regino2020discovering,\n  title = {Discovering Semantically Broken Links in LOD Datasets.},\n  author = {Regino, Andr{\\'e} Gomes and dos Reis, J{\\'u}lio Cesar},\n  booktitle = {Workshop Managing the Evolution and Preservation of the Data Web (MEPDaW'20) co-located at the 19th International Semantic Web Conference (ISWC’20), virtual conference.},\n  pages = {17--26},\n  year = {2020},\n  timestamp = {Fri, 10 Mar 2023 00:00:00 +0100},\n  biburl = {https://dblp.org/rec/conf/semweb/ReginoR20.bib},\n  bibsource = {dblp computer science bibliography, https://dblp.org},\n  url = {https://ceur-ws.org/Vol-2821/paper3.pdf},\n  publisher = {CEUR-WS.org},\n  volume = {2821},\n  series = {{CEUR} Workshop Proceedings},\n}\n\n
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\n \n\n \n \n \n \n \n Lodmf: A linked open data maintenance framework.\n \n \n \n\n\n \n Regino, A. G.; dos Reis, J. C.; and Bonacin, R.\n\n\n \n\n\n\n In 2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), pages 263–268, 2020. IEEE, IEEE\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{regino2020lodmf,\n  title = {Lodmf: A linked open data maintenance framework},\n  author = {Regino, Andr{\\'e} Gomes and dos Reis, Julio Cesar and Bonacin, Rodrigo},\n  booktitle = {2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)},\n  pages = {263--268},\n  year = {2020},\n  organization = {IEEE},\n  doi = {10.1109/WETICE49692.2020.00058},\n  timestamp = {Mon, 03 Jan 2022 00:00:00 +0100},\n  biburl = {https://dblp.org/rec/conf/wetice/ReginoRB20.bib},\n  bibsource = {dblp computer science bibliography, https://dblp.org},\n  publisher = {{IEEE}},\n}\n\n
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\n \n\n \n \n \n \n \n \n Link Maintenance in the Semantic Web.\n \n \n \n \n\n\n \n Regino, A. G.; and dos Reis, J. C.\n\n\n \n\n\n\n In XIII Seminar on Ontology Research in Brazil (ONTOBRAS) - IV Doctoral and Masters Consortium on Ontologies. Vitoria, Brazil, volume 2728, of CEUR Workshop Proceedings, pages 263–268, 2020. CEUR-WS.org. Best M.Sc. Paper Award\n \n\n\n\n
\n\n\n\n \n \n \"LinkPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{regino2020lodmf,\n  title = {Link Maintenance in the Semantic Web},\n  author = {Regino, Andr{\\'e} Gomes and dos Reis, Julio Cesar},\n  booktitle = {XIII Seminar on Ontology Research in Brazil (ONTOBRAS) - IV Doctoral and Masters Consortium on Ontologies. Vitoria, Brazil},\n  pages = {263--268},\n  year = {2020},\n  publisher = {CEUR-WS.org. Best M.Sc. Paper Award},\n  timestamp = {Fri, 10 Mar 2023 00:00:00 +0100},\n  biburl = {https://dblp.org/rec/conf/ontobras/ReginoR20.bib},\n  bibsource = {dblp computer science bibliography, https://dblp.org},\n  url = {https://ceur-ws.org/Vol-2728/master3.pdf},\n  volume = {2728},\n  series = {{CEUR} Workshop Proceedings},\n  _bib2doi_selected = {dblp:/rec/conf/ontobras/ReginoR20.bib},\n}\n\n
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\n  \n 2019\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n Understanding Link Changes in LOD via the Evolution of Life Science Datasets.\n \n \n \n\n\n \n Regino, A. G.; Matsoui, J. K. R.; dos Reis, J. C.; Bonacin, R.; Morshed, A.; and Sellis, T.\n\n\n \n\n\n\n In Hasnain, A.; Novácek, V.; Dumontier, M.; and Rebholz-Schuhmann, D., editor(s), Proceedings of the Workshop on Semantic Web Solutions for Large-Scale Biomedical Data Analytics co-located with 18th International Semantic Web Conference (ISWC 2019), Auckland, New Zealand, October 27th, 2019, volume 2477, of CEUR Workshop Proceedings, pages 40–54, 2019. CEUR-WS.org\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{Regino:Sewebmeda,\n  author = {Andr{\\'{e}} Gomes Regino and Julio Kiyoshi Rodrigues Matsoui and J{\\'{u}}lio C{\\'{e}}sar dos Reis and Rodrigo Bonacin and Ahsan Morshed and Timos Sellis},\n  editor = {Ali Hasnain and V{\\'{\\i}}t Nov{\\'{a}}cek and Michel Dumontier and Dietrich Rebholz{-}Schuhmann},\n  title = {Understanding Link Changes in {LOD} via the Evolution of Life Science Datasets},\n  booktitle = {Proceedings of the Workshop on Semantic Web Solutions for Large-Scale Biomedical Data Analytics co-located with 18th International Semantic Web Conference {(ISWC} 2019), Auckland, New Zealand, October 27th, 2019},\n  series = {{CEUR} Workshop Proceedings},\n  volume = {2477},\n  pages = {40--54},\n  publisher = {CEUR-WS.org},\n  year = {2019},\n  timestamp = {Fri, 10 Mar 2023 00:00:00 +0100},\n  biburl = {https://dblp.org/rec/conf/semweb/ReginoMRBMS19.bib},\n}\n\n
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