Entity-Based Relevance Feedback for Document Retrieval

Eilon Sheetrit, Fiana Raiber, Oren Kurland
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Abstract

There is a long history of work on using relevance feedback for ad hoc document retrieval. The main types of relevance feedback studied thus far are for documents, passages and terms. We explore the merits of using relevance feedback provided for entities in an entity repository. We devise retrieval methods that can utilize relevance feedback provided for tokens whether entities or terms. Empirical evaluation shows that using entity relevance feedback falls short with respect to utilizing term feedback on average, but is much more effective for difficult queries. Furthermore, integrating term and entity relevance feedback is of clear merit; e.g., for augmenting minimal document feedback. We also contrast approaches to presenting entities and terms for soliciting relevance feedback.
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基于实体的文档检索相关反馈
在使用相关反馈进行特殊文档检索方面已有很长的研究历史。目前研究的相关反馈类型主要有文献、段落和术语。我们探讨了在实体存储库中使用为实体提供的相关反馈的优点。我们设计了检索方法,可以利用为实体或术语的令牌提供的相关反馈。经验评估表明,平均而言,使用实体相关反馈与使用术语反馈相比不足,但对于困难的查询更有效。此外,将术语和实体相关反馈相结合的方法具有明显的优点;例如,增加最小的文档反馈。我们还对比了呈现实体和征求相关反馈的术语的方法。
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