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Exploitation of Query Sentences using Specific Weighting in Support-Sentence Retrieval

机译:使用特定加权在支持句检索中的查询句子的利用

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Our goal is to develop a support-sentence retrieval system that retrieves sentences relevant to a given theme and then, classifies them into relevant types, such as agreement, contradiction, refinement, and supplement. This paper focuses on the first step, a sentence retrieval module. Lexical and typed dependency matching are used to compute the similarity between two sentences. A new query term weighting scheme based on the specificity of the terms is proposed and combined with ordinary IDF weighting for a better performance. Experimental results indicate that our method achieves 34% higher precision than the traditional TF-ISF method..
机译:我们的目标是开发一个支持句子检索系统,检索与给定主题相关的句子,然后将它们分类为相关类型,例如协议,矛盾,细化和补充。本文侧重于第一步,句子检索模块。词汇和键入的依赖关系匹配用于计算两个句子之间的相似性。提出了一种基于术语特异性的新查询术语加权方案,并与普通的IDF加权组合,以获得更好的性能。实验结果表明,我们的方法比传统的TF-ISF方法达到34%的精度。

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