首页> 中文期刊>信息网络安全 >基于分类的中文微博热点话题发现方法研究

基于分类的中文微博热点话题发现方法研究

     

摘要

Smart-phones and micro-blog client reinforce the micro-blog media features. Therefore, Micro-blog hot topic real-time detection can provide valuable research results in relevant ifelds. The paper introduces a real-time hot micro-blog topic detection method based on keywords classiifcation. Filtered micro-blog messages were classiifed according to keywords. A multi-weight function based on the word frequency and growth in the time window was used to extract the key words of micro-blog information. An improved single-pass clustering algorithm based on same-text conditional probability was used to ifnd the micro-blog hot topic. The results show that the approach is effect in clustering micro-blog hot topic in real time.%智能手机和微博客户端强化了微博的媒体特性,实时发现微博话题具有现实意义。文章提出了一种基于关键字分类的中文微博热点话题发现方法,通过关键字对微博信息进行筛选和归类,以时间窗内词频和增长速度构造赋权函数提取主题词,词汇的同文本条件概率作为相似度判定依据,基于改进的单遍聚类算法进行主题词聚类。对系统运行结果分析表明,该方法可以实时有效地聚类发现微博热点话题。

著录项

相似文献

  • 中文文献
  • 外文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号