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计算机工程

• 先进计算与数据处理 • 上一篇    下一篇

基于HDP模型的领域微博主题演化研究

高永兵 1,杨利莹 1,胡文江 1,马占飞 2   

  1. (1.内蒙古科技大学 信息工程学院,内蒙古 包头 014010; 2.包头师范学院 信息工程系,内蒙古 包头 014010)
  • 收稿日期:2017-02-23 出版日期:2018-02-15 发布日期:2018-02-15
  • 作者简介:高永兵(1974—),男,副教授、硕士,主研方向为计算语言学、Web数据管理;杨利莹,硕士研究生;胡文江,教授;马占飞,教授、博士。
  • 基金资助:
    国家自然科学基金(61163025);内蒙古自治区自然科学基金(2015MS0621)。

Research on Domanial Microblog Topic Evolution Based on HDP Model

GAO Yongbing  1,YANG Liying  1,HU Wenjiang  1,MA Zhanfei  2   

  1. (1.College of Information Engineering,Inner Mongolia University of Science and Technology,Baotou,Inner Mongolia 014010,China;2.Department of Information Engineering,Baotou Teachers’ College,Baotou,Inner Mongolia 014010,China)
  • Received:2017-02-23 Online:2018-02-15 Published:2018-02-15

摘要: 领域微博中包含较多的专业领域信息,并且随时间表现出较强的演化性。为分析领域的主题演化情况,构建一个基于分层Dirichlet过程(HDP)的DM-HDP模型。以用户为单位抽取领域相关的微博,利用微博的领域特征和时间特征,提取领域相关带有明显时间特征的微博并自动挖掘其主题分布,最终构建领域主题演化分析过程。实验结果表明,基于DM-HDP模型的分析方法能够表现领域微博主题的演化过程,与基于LDA和HDP模型的方法相比,在内容困惑度和模型复杂度等方面均具有明显优势。

关键词: 领域微博, 主题挖掘, 分层Dirichlet模型, DM-HDP模型, Gibbs采样, 主题演化

Abstract: Domanial microblog contains much professional information that show a strong evolution over time.In order to analyze the topics of professional microblog automatically,a domanial microblog topic evolution method based on Hierarchical Dirichlet Process(HDP) model is built.Firstly,domain-related microblog is extracted with the individual user as the unit.Then,accurate extraction of domain-related microblog with distinct temporal features and automatic mining of its topics using domain features and temporal features.At last,the process of domanial topics evolution analysis is constructed.Experimental results show that the method based on the DM-HDP model can show the evolution of the field of microblog,and compared with the methods that based on the LDA and HDP model,it has obvious advantages in terms of content confusion and model complexity.

Key words: domanial microblog, topic mining, hierarchical Dirichlet model, DM-HDP model, Gibbs sampling, topic evolution

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