Abstract

A common cause of retrieval failure in case-based reasoning (CBR) approaches to product recommendation is that the retrieved cases, usually those that are most similar to the target query, are not sufficiently representative of compromises that the user may be prepared to make. We present a new approach to retrieval in which similarity and compromise play complementaryroles, thereby increasing the likelihood that one of the retrieved cases will be acceptable to the user. We also show howthe approach can be extended to address the requirements of domains in which the user is not just seeking a single item thatclosely matches her query, but would like to be informed of all items that are likely to be of interest.

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