文献类型：会议论文

英文题名：Blog topic detection based on the model

作者：Kuang, Tao[1]; Zhu, Shan Hong[1,2]

第一作者：邝涛

机构：[1] School of Computer and Information Engineering, Xinxiang university, Henan, China; [2] International School of Software, Wuhan University, Wuhan, China

第一机构：新乡学院计算机与信息工程学院

会议论文集：Progress in Applied Sciences, Engineering and Technology

会议日期：May 20, 2014 - May 21, 2014

会议地点：Qingdao, China

语种：英文

外文关键词：Blogs - Semantics - Tracking (position) - Vector spaces

摘要：Constructing and updating model from blog is also the process of topic detection and tracking, then, a detecting method of topics on blog based on model is proposed. It includes the use of measuring method Based on the event information to cluster for post and topic information to cluster event set (blog) which is combined with semantic vector space model, the use of the main idea of information granularity of topic detection and tracking algorithm has to be used and improved in order to generate the final clustering. The experimental results show that the algorithm has an accurate result in blog topic detection. ? (2014) Trans Tech Publications, Switzerland.