An efficient approach to iterative browsing and retrieval for case-based reasoning

A case base is a repository of past experiences that can be used for problem solving. Given a new problem, expressed in the form of a query, the case base is browsed in search of “similar” or “relevant” cases. One way to perform this search involves the iterative evaluation of a series of queries against the case base, where each query in the series is obtained by restricting or relaxing the preceding query.The paper considers alternative approaches for implementing iterative browsing in case-based reasoning systems, including a naive algorithm, which evaluates each query independent of earlier evaluations, and an incremental algorithm, which reuses the results of past query evaluations to minimize the computation required for subsequent queries. In particular, the paper proposes an efficient algorithm for case base browsing and retrieval using database techniques for view maintenance. In addition, the paper evaluates the performance of the proposed algorithm with respect to alternative approaches considering two perspectives: (i) experimental efficiency evaluation using diverse application domains, and (ii) scalability evaluation using the performance model of the proposed system.