文献类型：会议论文

英文题名：The blog topic detection research based on bursty word

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：Signal detection

摘要：The emergence of blog hot topic means that the user's interest,participation behavior and various media report coverage reach to its climax, a detecting method of topics on blog based on blog bursty words is proposed. It includes the use of word similarity measure and text clustering analysis which is combined with design strategy in specific period, the use of the main idea of the sudden vocabulary hot topic detection algorithm has to be used and improved in order to generate the final clustering. The experimental results show that the algorithm can obtain an accurate blog topic detection results. ? (2014) Trans Tech Publications, Switzerland.