Retrieving Cases from Relational Data-Bases: Another Stride Towards Corporate-Wide Case-Base Systems

Abstract

Vital information for corporate activities is generally stored in large data-bases. While conventional dat~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 dat~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.