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Coverage-optimised retrieval (CORE) is a new case-based reasoning (CBR) approach to product recommendation which ensures that for any case that is acceptable to the user, one of the recommended cases is at least as good in an objective sense and so also likely to be acceptable. Similarity to the users query, the standard criterion on which recommendations are based in CBR, is only one of several preference criteria according to which a given case may be considered at least as good as another in CORE. We present a detailed analysis of retrieval in CORE and the trade-off between user satisfaction and cognitive load in the approach. [Copyright &y& Elsevier]

In applications of interactive case-based reasoning (CBR) such as help-desk support and recommender systems, a problem that often affects retrieval performance is the inability to distinguish between cases that have different solutions. For example, it is not unusual in recommender systems for two distinct products or services to have the same values for all attributes in the case library. While it is unlikely that both solutions are equally suited to the user''s requirements, the system cannot help the user to choose between them. This problem, which we refer to as inseparability, can also arise as a result of incomplete data in the target problem presented for solution by a CBR system. We present an in-depth analysis of the inseparability problem, its relationship to the problem of incomplete data, and its impact on retrieval performance. [Copyright &y& Elsevier]