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
fDate :
June 29 2010-July 1 2010
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;
Conference_Titel :
Communication Systems, Networks and Applications (ICCSNA), 2010 Second International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-7475-2
DOI :
10.1109/ICCSNA.2010.5588684
