Ranking algorithms for hierarchical similarity metrics
نویسنده
چکیده
Case retrieval for e-commerce product recommendation is an application of CBR that demands particular attention to efficient implementation. Users expect quick response times from on-line catalogs, regardless of the underlying technology. In FindMe systems research, the cost of metric application has been a primary impediment to efficient retrieval. This paper describes several types of general and special-purpose ranking algorithms for case retrieval and evaluates their impact on retrieval efficiency with the Entree restaurant recommender.
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تاریخ انتشار 2001