Abstract
With the rapid development of case-based reasoning (CBR) techniques such as case retrieval and case adaptation, CBR has been widely applied to various real-world applications. A successful case-based reasoning system requires a high-quality case base, which provides rich and efficient solutions for solving real-world problems. How to automatically create and manage such a case base is a vital but unsolved problem. This paper tackles this important problem. We proposed a methodology for creating cases from readily available large-sized databases, which were collected in the routine operations. Building on techniques from case-based reasoning and natural language processing, we present a methodology for automatically creating cases at initial stage of a CBR system development. After the detailed description of the methodology, we introduce a case study for validating the usefulness of the methodology. The experimental results show that the proposed methodology significantly reduces the human effort required for authoring cases, and we are able to automatically create the high-quality cases for diagnostic CBR systems from historic maintenance and operational data at the initial stage of system development.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Zaluski M, Japkowicz N, Matwin S (2003) Case authoring from text historical experiences. In: Proceedings of the sixteenth Canadian conference on artificial intelligence (AI’2003). Dalhousie University, Halifax, Nova Scotia, Canada
Ferrario MA, Smyth B (2000) Collaborative maintenance—a distributed, interactive case-based maintenance strategy. In: Proceedings of advances in case-based reasoning: fifth European workshop EWCBR. Trento, Italy, pp 393–405
Yang Q, Cheng H (2003) Case mining from large databases. In: Proceedings of 5th international conference on case-based reasoning, ICCBR. Trondheim, Norway
Lehane M, Dubé F, Halasz M, Orchard R, Wylie R, Zaluski M (1998) Integrated diagnostic system (IDS) for aircraft fleet maintenance. In: Proceedings of the AAAI’98 workshop: case-bases reasoning integrations. Madison, WI
Yang C, Orchard R, Farley B, Zaluski M (2003) Authoring cases from free-text maintenance data. In: Proceeding of IAPR international conference on machine learning and data mining (MLDM 2003). Leipzig, Germany, pp 131–140
Farley B (1999) From free-text repair action messages to automatic case generation. In: Proceedings of AAAI spring symposium: AI in equipment maintenance service and support. Technical Report SS-99-04, Menlo Park, CA, AAAI Press, pp 109–118
Farley B (2001) Extracting information from free-text aircraft repair notes, artificial intelligence for engineering design, analysis and manufacture. Cambridge University Press 0890-0604/01, I5, pp 295–305
Aha DW, Breslow LA (1997) Refining conversational case libraies. In: Proceedings of int’l conference of case-based reasoning. RI, USA, pp 267–278
Minor M, Hanft A (2000) The life cycle of test cases in a CBR system. In: Proceedings of advances in case-based reasoning: 5th European workshop. EWCBR 2000, Trento, Italy, pp 455–466
Smyth B (1998) Case-based maintenance. In: Proceedings of the 11th international conference on industry and engineering applications of AI and expert systems. Castellon, Spain
Zhu J, Yang Q (1999) Remembering to add: competence persevering case-addition policy for case-base maintenance. In: Proceedings of the 16th int’l joint conference on AI. Stockholm, Sweden, pp 234–239
Smyth B (1995) Remembering to forget: a competence persevering deletion policy for case-based reasoning systems. In: Proceedings of the 14th int’l joint conference on AI. Morgan-Kaufmann, pp 377–382
Racine K, Yang Q (1996) On the consistency management for large case bases: the case for validation. In: Proceedings of AAAI-96 workshop on knowledge base validation
Portinale L, Torasso P (2000) Automated case base management in a multi-model reasoning system. In: Proceedings of advances in case-based reasoning: 5th European workshop, EWCBR. Trento, Italy, pp 234–246
Wylie R, Orchard R, Halasz M, Dubé F (1997) IDS: improving aircraft fleet maintenance. In: Proceedings of the 14th national conference on artificial intelligence. Calif, USA, pp 1078–1085
Grover G, Klein E, Oullum G, Sag I (1985) Generalized phrase structure grammar. Backwell, Oxford
Author information
Authors and Affiliations
Corresponding author
Additional information
Dr. Chunsheng Yang is a Research Officer at the Institute for Information Technology of the National Research Council of Canada. He is interested in data mining, reasoning technologies such as case-based reasoning, rule-based reasoning and hybrid reasoning, multi-agent systems, and distributed computing. He received an Hons. B.Sc. in Electronic Engineering from Harbin Engineering University, China, an M.Sc. in computer science from Shanghai Jiao Tong University, China, and a Ph.D. from National Hiroshima University, Japan. He worked with Fujitsu Inc., Japan, as a Senior Engineer and engaged on the development of ATM Network Management Systems. He was an Assistant Professor at Shanghai Jiao Tong University from 1986 to 1990 working on Hypercube Distributed Computer Systems. Dr. Yang has been the author for over 30 papers and book chapters published in the referred journals and conference proceedings. He was a Program Co-Chair for the 17th International Conference on Industry and Engineering Applications of Artificial Intelligence and Expert Systems. Dr. Yang is a guest editor for the International Journal of Applied Intelligence. He has served Program Committees for many conferences and institutions, and has been a reviewer for many conferences, journals, and organizations, including Applied Intelligence, NSERC, IEEE Trans., ACM KDD, PAKDD, AAMAS, IEA/AIE and so on. Dr. Yang is a senior IEEE member and ACM member.
Benoit Farley is a research officer at the Institute for Information Technology of the National Research Council of Canada. He received his B. Appl. Sc. and his Master degree in Telecommunications at the Universitè de Sherbrooke in the province of Quèbec, Canada. After a number of years in computer-assisted learning and training, he has been working for the last twenty years in the field of natural language processing and understanding. His current research focuses on technolinguistic tools for aboriginal languages, more specifically Inuktitut, the language of the Inuit.
Bob Orchard is a Senior Research Officer at the National Research Council of Canada. There he is a member of the Integrated Reasoning Group of the Institute for Information Technology. He received an M.Sc. in Computer Science from the University of Western Ontario in 1974 and an Hons. B.Sc. in Mathematics from Queen’s University in 1972. His research interests include fuzzy logic, expert systems, and evolutionary computing. The interest in fuzzy logic led to the development of FuzzyCLIPS (an extension to the CLIPS expert system tool from NASA) and the FuzzyJ Toolkit which are used to create fuzzy reasoning applications.
Rights and permissions
About this article
Cite this article
Yang, C., Farley, B. & Orchard, B. Automated case creation and management for diagnostic CBR systems. Appl Intell 28, 17–28 (2008). https://doi.org/10.1007/s10489-007-0039-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10489-007-0039-1