[1]ZHAO Wenqing,HOU Xiaoke.News topic recognition of Chinese microblog based on word cooccurrence graph[J].CAAI Transactions on Intelligent Systems,2012,7(5):444-449.
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CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
7
Number of periods:
2012 5
Page number:
444-449
Column:
学术论文—自然语言处理与理解
Public date:
2012-10-25
- Title:
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News topic recognition of Chinese microblog based on word cooccurrence graph
- Author(s):
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ZHAO Wenqing; HOU Xiaoke
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School of Control and Computer Engineering, North China Electric Power University, Baoding 071003, China
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- Keywords:
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microblog; news topics; topic recognition; keywords; word cooccurrence graph
- CLC:
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TP391.1
- DOI:
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- Abstract:
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The traditional topic detection algorithm is applied to longer texts such as: news website pages or blogs, causing it to be hard to deal with sparse microblog data effectively. In this paper, a method based on the word cooccurrence graph was provided to detect news topics of microblogs. Firstly, the relative word frequency and the word frequency increase rate were considered to extract new keywords from microblog text after pretreatment. Secondly, a word cooccurrence graph was built by cooccurrence degrees of keywords; each unconnected cluster in a word cooccurrence graph was taken as a news topic by calculating several keywords.These keywords contain much more information in each cluster, was used to represent a news topic of microblog. Finally, data analysis provided evidence on how the approach is most effective and also revealed the microblog data set recognized news topic recognition.