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Automatic Query Recommendation using Click-Through Data

机译:使用点击数据自动查询建议

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摘要

We present a method to help a user redefine a query suggesting a list of similar queries. The method proposed is based on click-through data were sets of similar queries could be identified. Scientific literature shows that similar queries are useful for the identification of different information needs behind a query. Unlike most previous work, in this paper we are focused on the discovery of better queries rather than related queries. We will show with experiments over real data that the identification of better queries is useful for query disambiguation and query specialization.
机译:我们提出一种方法来帮助用户重新定义查询,以建议类似查询的列表。所提出的方法基于可以识别相似查询集的点击数据。科学文献表明,类似的查询对于识别查询后的不同信息需求很有用。与大多数以前的工作不同,本文将重点放在发现更好的查询而不是相关查询上。我们将通过对真实数据的实验表明,更好的查询标识对于查询歧义消除和查询专业化很有用。

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