A New Web Text Clustering Algorithm Based on DFSSM

Author

Yang, Bingru ; Song, Zefeng ; Wang, Yinglong ; Song, Wei

Author_Institution

Sch. of Inf. Eng., Univ. of Sci. & Technol. Beijing, Beijing

fYear

2008

fDate

3-5 Aug. 2008

Firstpage

27

Lastpage

32

Abstract

A new algorithm of Web text clustering mining is presented, which is based on the Discovery Feature Sub-space Model (DFSSM). This algorithm includes the training stage of SOM and the clustering stage, which characterizes self-stability and powerful antinoise ability. It can distinguishes the most meaningful features from the Concept Space without the evaluation function. we have applied the algorithm to the modern long-distance education. Through the analysis of the experimental results, it is obvious that this algorithm can effective help users to get valuable information from WWW quickly.

Keywords

Internet; data mining; distance learning; pattern clustering; text analysis; Web text clustering mining algorithm; discovery feature subspace model; long-distance education; Algorithm design and analysis; Clustering algorithms; Clustering methods; Data mining; Electronic commerce; Extraterrestrial measurements; Filters; Hilbert space; Text mining; World Wide Web;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronic Commerce and Security, 2008 International Symposium on

Conference_Location

Guangzhou City

Print_ISBN

978-0-7695-3258-5

Type

conf

DOI

10.1109/ISECS.2008.110

Filename

4606018