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基于LDA模型和微博热度的热点挖掘
引用本文:唐晓波,向坤.基于LDA模型和微博热度的热点挖掘[J].图书情报工作,2014,58(5):58-63.
作者姓名:唐晓波  向坤
作者单位:武汉大学信息系统研究中心
基金项目:本文系国家自然科学基金项目“社会化媒体集成检索与语义分析方法研究”(项目编号:71273194)研究成果之一。
摘    要:分析传统LDA模型在进行微博热点挖掘时所得概率结果抽象且难以结合实际解释的缺点;考虑到微博本身的数据特点和信息论中信息量的观点,提出微博热度的概念,并将其引入到LDA模型的热点挖掘研究中,构建基于微博热度的LDA模型;通过API采集微博数据上的实验,证明新方法与旧方法具有相同的性能,而且能得到更直观的微博热度表,并得出更具有说服力的挖掘结论。

关 键 词:LDA  微博热度  主题模型  热点挖掘  
收稿时间:2014-01-19

Hotspot Mining Based on LDA Model and Microblog Heat
Tang Xiaobo,Xiang Kun.Hotspot Mining Based on LDA Model and Microblog Heat[J].Library and Information Service,2014,58(5):58-63.
Authors:Tang Xiaobo  Xiang Kun
Institution:Center for Studies of Information System, Wuhan University, Wuhan 430072
Abstract:This paper analyses shortcomings in the traditional LDA (Latent Dirichlet Allocation) model when performing microblog hotspot mining, which include that excavated probability results is abstract and is difficult to interpret. Taking into account the characteristics of the microblog and the viewpoint of the information quantity in information theory, it proposes the concept of microblog heat, introduces it into the hotspots mining research of the LDA model, and frams the LDA model based on microblog heat. With experiments on microblog data collected through API, this paper proves that the new method has the same performance compared to the old one, furthermore, it can express a more intuitive table of microblog heatand draw a more convincible conclusion.
Keywords:LDA  microblog heat  topic model  hotspot mining  
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