A novel method of topic detection and tracking for BBS

Author

Zhao, Yan ; Xu, Jungang

Author_Institution

Sch. of Inf. Sci. & Eng., Grad. Univ. of Chinese Acad. of Sci., Beijing, China

fYear

2011

fDate

27-29 May 2011

Firstpage

453

Lastpage

457

Abstract

Topic Detection and Tracking (TDT) has been studied for years, but most existing research is oriented to news web pages. Compared to news web pages, texts in Bulletin Board System (BBS) are more complicated and filled with user participation. In this paper, we propose a novel method of TDT for BBS, which mainly includes: a representation posts selection procedure based on post quality ranking and an efficient topic clustering algorithm based on candidate topic set. Experiment results demonstrate that our method significantly improves the performance of TDT in BBS environment on both accuracy and time complexity.

Keywords

Web sites; computational complexity; information services; pattern clustering; text analysis; BBS environment; TDT; bulletin board system; candidate topic set; news Web pages; post quality ranking; representation posts selection procedure; time complexity; topic clustering algorithm; topic detection and tracking; user participation; Accuracy; Neodymium; BBS; candidate topic set; clustering; representation posts selection; topic detection and tracking;

fLanguage

English

Publisher

ieee

Conference_Titel

Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference on

Conference_Location

Xi´an

Print_ISBN

978-1-61284-485-5

Type

conf

DOI

10.1109/ICCSN.2011.6014309

Filename

6014309