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A Topic Modeling Based Approach for Enhancing Corpus Querying

机译：基于主题建模的语料库查询增强方法

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摘要

In information retrieval, the accuracy of the retrieval process is mainly dependent on query terms selection; therefore, the user must choose the needed terms carefully and selectively. Traditionally, the process of selecting query terms is done manually. However, in the last two decades, a lot of research has been directed towards automating the process of choosing and enhancing query terms. In this article, a new novel approach is presented, which relies on topic modeling in query building and expansion. Two open source systems were selected to perform the experiments, results show that adding the topic's term to the user's query clearly improves its quality and thus, improves the ranking results.
机译：在信息检索中，检索过程的准确性主要取决于查询词的选择。因此，用户必须仔细有选择地选择所需的术语。传统上，选择查询词的过程是手动完成的。但是，在过去的二十年中，许多研究都针对于自动化选择和增强查询词的过程。在本文中，提出了一种新的新颖方法，该方法依赖于查询构建和扩展中的主题建模。选择了两个开源系统进行实验，结果表明，将主题词添加到用户查询中可以明显提高其质量，从而改善排名结果。

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