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
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;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.258708
