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Automatic query taxonomy generation for information retrieval applications

机译:用于信息检索应用程序的自动查询分类法生成

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摘要

It is crucial for information retrieval systems to learn more about what users search for in order to fulfil the intent of searches. This paper introduces query taxonomy generation, which attempts to organise users' queries into a hierarchical structure of topic classes. Such a query taxonomy provides a basis for the in-depth analysis of users' queries on a larger scale and can benefit many information retrieval systems. The proposed approach to this problem consists of two computational processes: hierarchical query clustering to generate a query taxonomy from scratch, and query categorisation to place newly-arrived queries into the taxonomy. The results of the preliminary experiment have shown the potential of the proposed approach in generating taxonomies for queries, which may be useful in various Web information retrieval applications.
机译:对于信息检索系统来说,了解有关用户搜索内容的更多信息以实现搜索意图至关重要。本文介绍了查询分类法生成,它试图将用户的查询组织为主题类的层次结构。这种查询分类法为大规模分析用户查询提供了基础,并且可以使许多信息检索系统受益。提出的解决此问题的方法包括两个计算过程:分层查询聚类以从头开始生成查询分类,以及查询分类以将新到达的查询放入分类中。初步实验的结果表明了该方法在生成查询分类法中的潜力,这可能在各种Web信息检索应用程序中很有用。

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