Searching the Web with Queries

作者:Zhixiang Chen, Xiannong Meng, Richard H. Fowler

摘要

In this paper we study the problem of searching the Web with online learning algorithms. We consider that Web documents can be represented by vectors of n boolean attributes. A search engine is viewed as a learner, and a user is viewed as a teacher. We investigate the number of queries a search engine needs from the user to search for a collection of Web documents. We design several efficient learning algorithms to search for any collection of documents represented by a disjunction (or a conjunction) of relevant attributes with the help of membership queries or equivalence queries.

论文关键词:Web search, on-line learning, vector space, relevance feedback, query complexity

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论文官网地址:https://doi.org/10.1007/BF03325104