Chinese text classification method based on NMF

Author

Zhang, Lei ; Xiang, Xuezhi

Author_Institution

Inf. & Commun. Eng. Coll., Harbin Eng. Univ., Harbin, China

Volume

2

fYear

2009

fDate

5-6 Dec. 2009

Firstpage

240

Lastpage

243

Abstract

Text document classification based on the semantic level is a hot issue in text processing presently. In this paper, a method based on NMF for Chinese text classification is presented. According to NMF, the term-document matrix is decomposed to capture the relation between terms. This method settled effectively the problems of synonym and polysemy. It experimentally shows that, compared with LSI based on SVD, this method has advantages of faster computing speed, less memory occupancy and improvement of classification precision when the dimension reduces markedly.

Keywords

information retrieval; matrix decomposition; singular value decomposition; text analysis; NMF; SVD; chinese text document classification method; nonnegative matrix factorization; polysemy; semantic level; singular value decomposition; synonym; term-document matrix; text processing; Dictionaries; Educational institutions; Image retrieval; Indexing; Information retrieval; Matrix decomposition; Surveillance; Testing; Text categorization; Text processing; NMF; SVD; text document classification;

fLanguage

English

Publisher

ieee

Conference_Titel

Test and Measurement, 2009. ICTM '09. International Conference on

Conference_Location

Hong Kong

Print_ISBN

978-1-4244-4699-5

Type

conf

DOI

10.1109/ICTM.2009.5413065

Filename

5413065