DocumentCode :
3178113
Title :
A method based on manifold learning and Bagging for text classification
Author :
Li, FengGang ; Fan, JiLi ; Wang, Li ; Zhang, HuLin ; Duan, Rui
Author_Institution :
Sch. of Manage., Hefei Univ. of Technol., Hefei, China
fYear :
2011
fDate :
8-10 Aug. 2011
Firstpage :
2713
Lastpage :
2716
Abstract :
In order to solve the problem of high dimension in text classification, the paper proposes a method based on manifold learning and Bagging for text classification which imports manifold learning algorithm for dimension reduction. And Bagging algorithm is introduced when training classifier to improve the accuracy of text classification. Experimental results demonstrate that effect of text dimension reduction by manifold learning algorithm in the pretreatment of text classification is better, and the performance of the classifier has improved significantly.
Keywords :
learning (artificial intelligence); pattern classification; text analysis; classifier training; dimension reduction; high dimension problem; manifold Bagging algorithm; manifold learning algorithm; text classification; text dimension; Bagging; Classification algorithms; Euclidean distance; Manifolds; Support vector machine classification; Text categorization; Training; Bagging; Isomap; dimension reduction; manifold learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
Conference_Location :
Deng Leng
Print_ISBN :
978-1-4577-0535-9
Type :
conf
DOI :
10.1109/AIMSEC.2011.6010811
Filename :
6010811
Link To Document :
بازگشت