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A Multi-dependency Language Modeling Approach to Information Retrieval

机译:信息检索的多依赖语言建模方法

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摘要

This paper presents a multi-dependency language modeling approach to information retrieval. The approach extends the basic KL-divergence retrieval approach by introducing the hybrid dependency structure, which includes syntactic dependency, syntactic proximity dependency and co-occurrence dependency, to describe dependencies between terms. Term and dependency language models are constructed for both document and query. The relevant between a document and a query is then evaluated by using the KL-divergence between their corresponding models. The new dependency retrieval model has been compared with other traditional retrieval models. Experiment results indicate that it produces significant improvements in retrieval effectiveness.
机译:本文提出了一种用于信息检索的多依赖语言建模方法。该方法通过引入混合依存关系结构(包括句法依存关系,句法接近度依存关系和共现依存关系)来描述术语之间的依存关系,从而扩展了基本的KL-散度检索方法。为文档和查询构建术语和依赖语言模型。然后,通过使用其相应模型之间的KL散度来评估文档和查询之间的相关性。新的依赖项检索模型已与其他传统的检索模型进行了比较。实验结果表明,它在检索效率方面产生了重大改进。

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