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The Bayesian Optimal Algorithm for Query Refinement in Information Retrieval

机译:信息检索中查询细化的贝叶斯优化算法

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摘要

To realize more efficient information retrieval it is critical to improve the user's original query, because novice users can not be expected to formulate precise and effective queries. Queries can often be improved by adding extra terms that appear in relevant documents but which were not included in the original query. This is called query expansion. Query refinement, a variant of query expansion, interactively recommends new terms related to the original query. Because previous research did not offer any criterion to guarantee optimality, this paper proposes an optimal algorithm for query refinement with reference to the Bayes criterion.
机译:为了实现更有效的信息检索,改善用户的原始查询至关重要,因为不能期望新手用户制定精确而有效的查询。通常可以通过添加出现在相关文档中但原始查询中未包含的额外术语来改进查询。这称为查询扩展。查询细化是查询扩展的一种形式,它交互式地推荐与原始查询有关的新术语。由于先前的研究没有提供任何保证最优性的准则,因此本文提出了一种基于贝叶斯准则的查询细化优化算法。

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