DocumentCode :
3243182
Title :
An Efficient Web Document Classification Algorithm Based on LPP and SVM
Author :
Wang, Ziqiang ; Liu, Yuxun ; Sun, Xia
Author_Institution :
Sch. of Inf. Sci. & Eng., Henan Univ. of Technol., Zhengzhou
fYear :
2008
fDate :
22-24 Oct. 2008
Firstpage :
1
Lastpage :
4
Abstract :
With the explosive growth of World Wide Web, it is of great importance to develop methods for the automatic classifying of large collections of documents. To efficiently tackle this problem, a novel document classification algorithm based on locality pursuit projection (LPP) and SVM is proposed in this paper. The high-dimensional document space are first mapped into lower-dimensional space with LPP, the SVM is then used to classify the documents into semantically different classes. Experimental results show that the proposed algorithm achieves much better performance than other classification algorithms.
Keywords :
Internet; document handling; pattern classification; support vector machines; Web document classification; World Wide Web; locality pursuit projection; support vector machine; Classification algorithms; Information retrieval; Information science; Large scale integration; Pursuit algorithms; Sun; Support vector machine classification; Support vector machines; Text categorization; Web sites;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2008. CCPR '08. Chinese Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2316-3
Type :
conf
DOI :
10.1109/CCPR.2008.91
Filename :
4663044
Link To Document :
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