摘要: Standard Information Retrieval Systems (IRS) can be used to retrieve information in response specific requests, but they have no powers of adaption particular users over repeated sessions. This paper describes a learning system which uses relevance feedback from probabilistic IRS incrementally evolve context for user, number online We demonstrate the implementation with an example, and argue that it help adapt user's needs, by using this influence document display selection.
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