A bottom-up method for constructing topic hierarchies

Yuhao Zhang, W. Mao, Xiaochen Li
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Abstract

In security-related applications, it is of great need to construct topic hierarchies from the data automatically. It can help us better understand the contents and structure of information and benefit many applications in security informatics. The existing topic hierarchy construction methods either need to specify the structure manually, or are not robust enough for sparse social media data such as microblog. In this paper, we propose an approach to automatically construct topic hierarchies from microblog data in a bottom up manner. We first detect the fine grained topics and then build the topic structure based on a multi-branch hierarchical construction method. We conduct a preliminary empirical study based on Weibo data. The experimental results show that the hierarchical topic structure generated by our method can provide meaningful results.
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用于构造主题层次结构的自底向上方法
在与安全相关的应用中,从数据中自动构造主题层次结构是非常必要的。它可以帮助我们更好地理解信息的内容和结构,有利于安全信息学的许多应用。现有的主题层次结构构建方法要么需要手工指定结构,要么对于微博等稀疏的社交媒体数据鲁棒性不够。本文提出了一种基于自底向上的微博数据自动构建主题层次结构的方法。我们首先检测细粒度主题,然后基于多分支分层构建方法构建主题结构。我们基于微博数据进行了初步的实证研究。实验结果表明,该方法生成的分层主题结构能够提供有意义的结果。
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