Cluster based Detection and Analysis of Internet Topics

摘要：

Internet topic detection and classification is an intelligent information access technology. It studies how to detect new events and classify sentiment of the content. Classical detection and analysis system of internet topics has low analysis efficiency and large process delay. The functions of cluster-based analysis system are internet data collection, realtime analysis and off-line data analysis. Experimental results show that the Average Job Time (AJT) and Average Waiting Time (AWT) for jobs in case of Service Cluster are comparatively lesser with respect to Physical Server, and the Service Cluster shortens the service failover time by 93.4％.

关键词： internet topic data analysis Job Scheduling Cluster

作者: Jiao Wu Bin Zhang Chao Li Weihua Gao Jinsong Liu

作者单位: News Center Hebei University Baoding, China Network Center Hebei University Baoding, China

会议类型: 国际会议

会议名称: 2011 Fourth International Symposium on Computational Interlligence and Design 第四届计算智能与设计国际会议 ISCID 2011

会议地点: 杭州

会议语种:英文

页码: 751-754

在线出版日期: 2011-10-28（万方平台首次上网日期，不代表论文的发表时间）