A relational model of data for large shared data banks
Communications of the ACM
Case-based planning: an integrated theory of planning, learning and memory
Case-based planning: an integrated theory of planning, learning and memory
A hybrid CBR-IR approach to legal information retrieval
ICAIL '95 Proceedings of the 5th international conference on Artificial intelligence and law
The Wasabi Personal Shopper: a case-based recommender system
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
An Efficient Aproach to Similarity-Based Retrieval on Top of Relational Databases
EWCBR '00 Proceedings of the 5th European Workshop on Advances in Case-Based Reasoning
A Fuzzy Case Retrieval Approach Based on SQL for Implementing Electronic Catalogs
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
Ranking Algorithms for Costly Similarity Measures
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Case-method: a methodology for building large-scale case-based systems
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Detecting discontinuities in case-bases
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
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Vital information for corporate activities is generally stored in large databases. While conventional data-base management systems offer limited query flexibility, systems capable of generating similarity-based queries, such as those seen in case-based reasoning research, would certainly enhance the utility of data resources. This paper describes a method for building case-based systems using a conventional relational data-base (RDB). The core of the algorithm is a novel approach to similarity computing in which database query form similarities, rather than similarities of individual cases, are computed. The method uses Standard Query Language (SQL) to achieve nearest neighbor matching, thus allowing similarity-based database retrieval. It has been implemented as a part of the CARET case retrieval tool and evaluated through the use of a newly developed corporate-wide case-based system for a software quality control domain. Experiments have shown the proposed method to provide retrieval results equivalent to those of non-RDB implementation at a sufficiently fast response time.