DocumentCode
2889699
Title
An Optimal SVM-Based Text Classification Algorithm
Author
Wang, Zi-qiang ; Sun, Xia ; Zhang, De-Xian ; Li, Xin
Author_Institution
Sch. of Inf. & Eng., Henan Univ. of Technol., Zhengzhou
fYear
2006
fDate
13-16 Aug. 2006
Firstpage
1378
Lastpage
1381
Abstract
The goal of a text classification system is to determine whether a given document belongs to which of the predefined categories. An optimal SVM algorithm for text classification via multiple optimal strategies is proposed in this paper. The experimental results indicate that the proposed optimal classification algorithm yields much better performance than other conventional algorithms
Keywords
feature extraction; optimisation; support vector machines; text analysis; document classification; feature selection; optimal SVM-based text classification algorithm; predefined categories; Classification algorithms; Cybernetics; Electronic mail; Frequency; Machine learning; Machine learning algorithms; Organizing; Statistical analysis; Sun; Support vector machine classification; Support vector machines; Text categorization; Web sites; SVM; Text classification; optimal strategies;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location
Dalian, China
Print_ISBN
1-4244-0061-9
Type
conf
DOI
10.1109/ICMLC.2006.258708
Filename
4028279
Link To Document