DocumentCode
528438
Title
Document clustering algorithm based on NMF and SVDD
Author
Wang, Ziqiang ; Zhang, Qingzhou ; Sun, Xia
Author_Institution
Sch. of Inf. Sci. & Eng., Henan Univ. of Technol., Zhengzhou, China
Volume
1
fYear
2010
fDate
June 29 2010-July 1 2010
Firstpage
192
Lastpage
195
Abstract
Document clustering is one of the most important research areas of data mining due to its wide application in many fields. To efficiently cope with this problem, a novel document clustering algorithm based on nonnegative matrix factorization (NMF) and support vector data description (SVDD) is proposed in this paper. Experimental results on two well-known document data sets demonstrate the effectiveness of the proposed document clustering algorithm.
Keywords
computer software; data mining; document handling; matrix decomposition; pattern clustering; support vector machines; NMF; SVDD; data mining; document clustering algorithm; document data set; nonnegative matrix factorization; support vector data description; Accuracy; Bioinformatics; Indexes; World Wide Web; data mining; document clustering; nonnegative matrix factorization; support vector data description;
fLanguage
English
Publisher
ieee
Conference_Titel
Communication Systems, Networks and Applications (ICCSNA), 2010 Second International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-7475-2
Type
conf
DOI
10.1109/ICCSNA.2010.5588684
Filename
5588684
Link To Document