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A New Web Text Clustering Algorithm Based on DFSSM

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4 Author(s)
Bingru Yang ; Sch. of Inf. Eng., Univ. of Sci. & Technol. Beijing, Beijing ; Zefeng Song ; Yinglong Wang ; Wei Song

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.

Published in:

Electronic Commerce and Security, 2008 International Symposium on

Date of Conference:

3-5 Aug. 2008