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Statistical Methods based on Semantic Similarity of Topics Related to Microblogging

机译:基于与微博相关主题的语义相似度的统计方法

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摘要

Existing topic tracking methods are mostly for news and forum data, which lack of statistical methods for microblogging on relevant topics. Combined with characteristics of micro-blog information, the paper proposes a microblogging statistical methods based on semantic similarity. Firstly by building topic semantic model and then use the HowNet semantic similarity calculation of two terms, and measures the relevance of the topic and microblogging. Finally statistics method is provided on the degree of correlation. Experiments show that novel method works on the problem soundly.
机译:现有的主题跟踪方法主要用于新闻和论坛数据,而缺少用于对相关主题进行微博的统计方法。结合微博信息的特点,提出了一种基于语义相似度的微博统计方法。首先通过建立主题语义模型,然后使用两个词的HowNet语义相似度计算,来衡量主题与微博的相关性。最后给出了相关度的统计方法。实验表明,新颖的方法可以很好地解决该问题。

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