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摘要
En 中文
E-commerce sites can have large, essentially unbounded, catalogs. With large catalogs comes increasing difficulty for buyers in making use of standard search and browsing facilities. Particularly in the case of casual or occasional buyers and in the case of complex products, the gap between a product's specifications and the buyer's understanding of need can be hard to bridge. An effective e-commerce catalog must map user needs to products that can fulfill them. This paper describes an interactive, incremental, case-based, critiquing approach to solving this problem. The approach is interactive and incremental, so it does not require that the user have a completely specified need at the start. The system is case-based in that it emphasizes products over features or constraints, and uses case-based reasoning techniques for its product retrieval. Finally, the approach is based on the critiquing of presented examples, each critique redirecting the search to home in on appropriate products.
Keyword:
case-based reasoning
electronic commerce
information retrieval
recommender systems
AI总结
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