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A semantic approach to concept lattice-based information retrieval

机译:基于概念格的信息检索的语义方法

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摘要

The volume of available information is growing, especially on the web, and in parallel the questions of the users are changing and becoming harder to satisfy. Thus there is a need for organizing the available information in a meaningful way in order to guide and improve document indexing for information retrieval applications taking into account more complex data such as semantic relations. In this paper we show that Formal Concept Analysis (FCA) and concept lattices provide a suitable and powerful support for such a task. Accordingly, we use FCA to compute a concept lattice, which is considered both a semantic index to organize documents and a search space to model terms. We introduce the notions of cousin concepts and classification-based reasoning for navigating the concept lattice and retrieve relevant information based on the content of concepts. Finally, we detail a real-world experiment and show that the present approach has very good capabilities for semantic indexing and document retrieval.
机译:可用信息的数量正在增长,尤其是在Web上,与此同时,用户的问题也在不断变化,越来越难以满足。因此,需要以有意义的方式来组织可用信息,以便在考虑诸如语义关系之类的更复杂数据的情况下,指导和改善信息检索应用的文档索引编制。在本文中,我们表明形式概念分析(FCA)和概念格为此类任务提供了合适而强大的支持。因此,我们使用FCA来计算概念晶格,该概念晶格既被视为组织文档的语义索引,又被视为模型术语的搜索空间。我们介绍了表亲概念和基于分类的推理的概念,用于导航概念格并基于概念的内容检索相关信息。最后,我们详细介绍了一个真实世界的实验,并表明该方法具有很好的语义索引和文档检索功能。

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