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现代图书情报技术  2013, Vol. 29 Issue (2): 57-62    DOI: 10.11925/infotech.1003-3513.2013.02.09
  情报分析与研究 本期目录 | 过刊浏览 | 高级检索 |
中文微博突发事件检测研究
王勇1, 肖诗斌1,2, 郭跇秀1, 吕学强1,2
1. 北京信息科技大学网络文化与数字传播北京市重点实验室 北京 100101;
2. 北京拓尔思信息技术股份有限公司 北京 100101
Research on Chinese Micro-blog Bursty Topics Detection
Wang Yong1, Xiao Shibin1,2, Guo Yixiu1, Lv Xueqiang1,2
1. Beijing Key Laboratory of Internet Culture and Digital Dissemination Research, Beijing Information Science and Technology University, Beijing 100101, China;
2. Beijing TRS Information Technology Co., Ltd., Beijing 100101, China
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摘要 从微博中准确而高效地挖掘出突发事件是近年来的研究热点。通过词频统计、词增长率计算和TF-PDF算法抽取突发词集,使用突发词表示文本并结合微博突发事件的描述特征进行文本过滤;提出一种“绝对聚类”算法,对描述突发事件的文本进行聚类,并通过微博的回复数和转发数加权计算热度,检测各类事件中热度最大的作为突发事件。检测准确率为92.60%,召回率为85.51%,F值为0.89。实验结果表明,相比于传统的突发事件检测方法,该方法能够比较准确地检测到微博中的突发事件,有一定的应用价值。
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王勇
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吕学强
关键词 突发事件突发词文本过滤绝对聚类    
Abstract:Much attention is paid to mining bursty topics accurately and efficiently from micro-blog nowadays. In this paper, a set of burst terms are extracted by counting the term frequency, calculating the growth rate of the terms and using Term Frequency-Proportional Document Frequency (TF-PDF) algorithm to measure the weight. And then micro-blog texts are described with the burst terms. Analyzing the characteristic that bursty topics propagate in the platform of micro-blog, the authors filter the texts that do not contribute to detect bursty topics. The paper proposes a novel clustering strategy of “Absolute Clustering” to cluster the micro-blog texts. By figuring up the hot spot of the texts with weighted value of reply and retweet number, the top 5 texts are extracted as the result of burst topics detection. The experiments show that the precision is 92.60%, the recall is 85.51% and the F-measure is 0.89. Contrast with the traditional method, the validity of the proposed method is proved.
Key wordsBursty topics    Burst terms    Filter    Absolute clustering
收稿日期: 2013-01-18     
:  TP311.6  
基金资助:本文系国家自然科学基金项目“基于本体的专利自动标引研究”(项目编号:61271304)、国家自然科学基金项目“网页内容真实性评价研究”(项目编号:61171159)、北京市教委科技发展计划重点项目暨北京市自然科学基金B类重点项目“面向领域的互联网多模态信息精准搜索方法研究”(项目编号:KZ201311232037)和国家科技支撑计划课题“增强型搜索引擎关键技术研究与示范”(项目编号:2011BAH11B03)的研究成果之一。
通讯作者: 王勇,wy514674793@126.com     E-mail: wy514674793@126.com
引用本文:   
王勇, 肖诗斌, 郭跇秀, 吕学强. 中文微博突发事件检测研究[J]. 现代图书情报技术, 2013, 29(2): 57-62.
Wang Yong, Xiao Shibin, Guo Yixiu, Lv Xueqiang. Research on Chinese Micro-blog Bursty Topics Detection. New Technology of Library and Information Service, DOI:10.11925/infotech.1003-3513.2013.02.09.
链接本文:  
http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.1003-3513.2013.02.09
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