Cluster Based Detection and Analysis of Internet Topics

Author

Wu, Jiao ; Gao, Weihua ; Zhang, Bin ; Liu, Jinsong ; Li, Chao

Author_Institution

News Center, Hebei Univ., Baoding, China

Volume

2

fYear

2011

fDate

28-30 Oct. 2011

Firstpage

371

Lastpage

374

Abstract

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, real-time 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%.

Keywords

Internet; pattern classification; pattern clustering; Internet topic clasification; Internet topic detection; average job time; average waiting time; cluster based detection; intelligent information access technology; Conferences; Data analysis; Data warehouses; Engines; Internet; Servers; Web pages; Cluster; Job Scheduling; data analysis; internet topic;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Design (ISCID), 2011 Fourth International Symposium on

Conference_Location

Hangzhou

Print_ISBN

978-1-4577-1085-8

Type

conf

DOI

10.1109/ISCID.2011.195

Filename

6079814