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Ontology Based Query Expansion with a Probabilistic Retrieval Model

机译:带有概率检索模型的基于本体的查询扩展

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This paper examines the use of ontologies for defining query context. The information retrieval system used is based on the probabilistic retrieval model. We extend the use of relevance feedback (RFB) and pseudo-relevance feedback (PF) query expansion techniques using information from a news domain ontology. The aim is to assess the impact of the ontology on the query expansion results with respect to recall and precision. We also tested the results for varying the relevance feedback parameters (number of terms or number of documents). The factors which influence the success of ontology based query expansion are outlined. Our findings show that ontology based query expansion has had mixed success. The use of the ontology has vastly increased the number of relevant documents retrieved, however, we conclude that for both types of query expansion, the PF results are better than the RFB results.
机译:本文研究了使用本体来定义查询上下文。所使用的信息检索系统基于概率检索模型。我们使用新闻域本体中的信息来扩展相关性反馈(RFB)和伪相关性反馈(PF)查询扩展技术的使用。目的是评估关于回忆和准确性的本体对查询扩展结果的影响。我们还测试了用于更改相关性反馈参数(术语数或文档数)的结果。概述了影响基于本体的查询扩展成功的因素。我们的发现表明,基于本体的查询扩展取得了不同的成功。本体的使用极大地增加了检索到的相关文档的数量,但是,我们得出结论,对于两种查询扩展类型,PF结果都比RFB结果更好。

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