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Subtopic Based Topic Evolution Analysis

机译:基于子主题的主题演化分析

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摘要

Traditional topic tracking approaches can obtain the relevant stories. However, the relationship between stories occurred during the topic developing process can not be exhibited clearly. By analyzing the evolution of the topic, the concept subtopic is put forward and the focus of topic evolution analysis is subtopic instead. Four levels topic model is constructed. The subtopic detection algorithm, time slices partition algorithm and topic evolution analysis algorithm are designed. These algorithms make use of the temporal characteristic of topic, partition the news stories into time slices and compute the similarity of these units. As a result, the relationships between the various subtopics in the process of the topic evolution are achieved. Experiments show our algorithms are effective.
机译:传统的主题跟踪方法可以获取相关故事。但是,在主题开发过程中发生的故事之间的关系无法清晰显示。通过分析主题的演变,提出了概念子主题,而将主题演变分析的重点放在了子主题上。构建了四个层次的主题模型。设计了子主题检测算法,时间片划分算法和主题演化分析算法。这些算法利用主题的时间特征,将新闻故事划分为时间片,并计算这些单元的相似度。结果,实现了主题演变过程中各个子主题之间的关系。实验表明我们的算法是有效的。

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