使用维基百科分类发现文本文档的主题

2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics Pub Date : 2015-08-26 DOI:10.1109/IHMSC.2015.68

Abdullah Bawakid

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引用次数: 2

摘要

本文描述了一种新的无监督方法，用于在维基百科的帮助下识别任何文本文档的主题。与其他算法相比，该算法仅依赖于维基百科的两个主要方面，即文章标题和分类结构。我们的算法没有使用维基百科文章的内部内容。我们在本文中描述了如何构建一个术语-类别向量，该向量定义了术语与维基百科概念的关联程度。我们还解释了在处理文本文档以发现其主题时如何使用此向量。我们通过尝试预测维基百科文章子集中最具代表性的类别来报告我们方法的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Using Wikipedia Categories for Discovering the Themes of Text Documents

This paper describes a new unsupervised approach for identifying the main themes of any text document with the aid of Wikipedia. In contrast to others, the proposed algorithm relies on merely two main aspects of Wikipedia, namely its articles titles and categories structure. The inner content of the articles of Wikipedia are not employed in our algorithm. We describe in this paper how to build a Term-Categories vector that defines how strong a term is associated to a Wikipedia concept. We also explain how this vector is employed when processing a text document to discover its main themes. We report the performance of our method by attempting to predict the most representative categories for a subset of Wikipedia articles.

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2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics

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