基于co-ICIB联合聚类的舆情监测系统设计  

Design of public sentiment monitoring system based on co-ICIB co-clustering

作　　者：刘永利[1] 吕克林[2] 刘静[1] 

机构地区：[1]河南理工大学计算机科学与技术学院,河南焦作454000 [2]河南省科学技术信息研究院,郑州450003

出　　处：《河南理工大学学报（自然科学版）》2013年第5期592-595,共4页Journal of Henan Polytechnic University（Natural Science）

基　　金：国家自然科学基金资助项目(61202286);国家社会科学基金资助项目(11CYY019);河南省社科联项目(SKL-2013-486);河南理工大学青年骨干教师资助项目

摘　　要：基于co-ICIB联合聚类的舆情监测系统的设计为舆情信息库,它通过联合聚类等数据挖掘算法可以快速及时地发现新的舆论热点.当舆论热点被确认,即在互联网上真正成为一个备受关注的话题时,文本分类算法可以将同一话题内的信息归类,有助于跟踪舆情的发展趋势.该舆情监测系统可为舆情监管部门提供原始舆情资料、数据性图表和建议性分析.A public sentiment monitoring system is designed, based on coICIB coclustering. The system col lects the information from micro blogs and blogs, creates public sentiment database and analyzes the hot points and development trend of public sentiment by such data mining algorithms as coclustering. Once hot points are confirmed, which means they become truly concentrated topics in Internet, text categorization algorithms could group the information of the same topic into one category and help the track trend of public sentiment. The results of the system could provide the original public sentiment data, data chart and suggestion analysis for a public sentiment supervision department.

关 键 词：自媒体 舆情 联合聚类 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]