Hot Topics Extraction from Chinese Micro-blog Based on Sentence

被引：1

作者：

Zhou, Chuanfeng ^{[1
]}

Zhang, Yuqing ^{[1
]}

Li, Beige ^{[1
]}

Li, Donghui ^{[1
]}

机构：

[1] China Univ Geosci, Sch Informat Engn, Beijing, Peoples R China

来源：

IEEE 12TH INT CONF UBIQUITOUS INTELLIGENCE & COMP/IEEE 12TH INT CONF ADV & TRUSTED COMP/IEEE 15TH INT CONF SCALABLE COMP & COMMUN/IEEE INT CONF CLOUD & BIG DATA COMP/IEEE INT CONF INTERNET PEOPLE AND ASSOCIATED SYMPOSIA/WORKSHOPS | 2015年

基金：

中央高校基本科研业务费专项资金资助;

关键词：

micro-blog; hot topic; sentence; opinion leader;

D O I：

10.1109/UIC-ATC-ScalCom-CBDCom-IoP.2015.128

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

the first micro-blog service appeared in China was Sina Weibo, it has developed very fast in recent years. Some hot topics have a significant impact on the public opinion formation and dissemination. Also, potential security risks are absolutely not being underestimated. In order to extract hot topics, this paper proposes an algorithm called CBOS (Clustering Based on Sentence) and compares it with the classic algorithm K-means and so on. The results show that CBOS is different; it offers a new perspective on people to extract hot topics. And the research indicates extracting hot topics by CBOS has a great precession and recall.

引用

页码：645 / 648

页数：4

共 25 条

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