Title :
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
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;
Conference_Titel :
Electronic Commerce and Security, 2008 International Symposium on
Conference_Location :
Guangzhou City
Print_ISBN :
978-0-7695-3258-5
DOI :
10.1109/ISECS.2008.110
