DocumentCode :
1676451
Title :
NMF-based method of text classification
Author :
Sun, Fuzhen ; Zhang, Kun
Author_Institution :
Coll. of Comput. Sci. & Technol., Shandong Univ. of Technol.Shandong, Zibo, China
fYear :
2010
Firstpage :
4312
Lastpage :
4316
Abstract :
This paper put forward a text classification method based oil NIYIF (Non-negative -Matrix Factorization), NMF-based analysis of the conceptual semantic space and the text rector dimensionality reduction- better explain the concept of the semantic vector, better reflect the local features of the text, comparison of two methods of generating conceptual semantic space based on NMF and SVD (Singular Value Decomposition). Experimental results show that the local conceptual semantic space generated based on NMF can be a better text classification accuracy.
Keywords :
matrix decomposition; pattern classification; singular value decomposition; text analysis; NMF-based method; conceptual semantic space; nonnegative matrix factorization; oil NIYIF; singular value decomposition; text classification method; text rector dimensionality reduction; Robustness; Visualization; NME text classification; SVD; conceptual semantic space;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
Type :
conf
DOI :
10.1109/WCICA.2010.5554018
Filename :
5554018
Link To Document :
بازگشت