Case Completion of Workflows for Process-Oriented Case-Based Reasoning. Müller, G. & Bergmann, R. In Goel, A., Diaz-Agudo, B., & Roth-Berghofer, T., editors, Case-Based Reasoning Research and Development - 24nd International Conference, ICCBR 2016, Atlanta, USA. Proceedings, volume 9969, of Lecture Notes in Artificial Intelligence, pages 295–310, 2016. Springer. The original publication is available at www.springerlink.com
Case Completion of Workflows for Process-Oriented Case-Based Reasoning [pdf]Paper  abstract   bibtex   
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_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}
}
Downloads: 0