标题:Micro-blog keyword extraction method based on graph model and semantic space
作者:Zhao, Hua ;Zeng, Qingtian
作者机构:[Zhao, Hua ;Zeng, Qingtian ] College of Information Science and Engineering, Shandong University of Science and Technology, Qingdao, 266590, China
来源:Journal of Multimedia
出版年:2013
卷:8
期:5
页码:611-617
DOI:10.4304/jmm.8.5.611-617
摘要:There have been many domain-specific keyword extraction researches, but micro-blog- oriented keyword extraction is just beginning. This paper researches into the keyword extraction from Chinese micro-blog. Taking the characteristics of micro-blog into account, such as short, topic divergence, etc., we propose a Chinese micro-blog keyword extraction method based on the combination of multi features. Firstly create the graph model based on the co-occurrence between words, get a kind of weight based on the created graph model. The weight based on the graph model is sometimes same. In order to solve this problem, this method secondly proposes to create the semantic space based on the topic detection method, and get the statistical weight based on the semantic space. Finally, we take the location of words into account during the extraction, which is proved to be a very effective feature. Experimental results show that the proposed keyword extraction method is very successful. © 2013 ACADEMY PUBLISHER.
收录类别:EI
资源类型:期刊论文
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