Title :
An Efficient SVM Classifier for Lopsided Corpora
Author :
Zhang, Xianfei ; Li, Bicheng ; WangShi ; LuoCheng
Author_Institution :
Zhengzhou Inf. Sci. & Technol. Inst.
Abstract :
This paper explores application of SVM to lopsided-corpora in text categorization. By means of integrating kernel caching with shrinking policies effectively, an improved SVM training algorithm for weight-calculation formula is proposed under the decomposition framework. Extensive experiments on lopsided-corpora have been conducted. The conclusion can make it possible to apply the improved SVM training algorithm to lopsided corpora in text categorization
Keywords :
learning (artificial intelligence); pattern classification; support vector machines; text analysis; SVM classifier; SVM training algorithm; decomposition framework; kernel caching; lopsided corpora; shrinking policy; support vector machine; text categorization; weight-calculation formula; Constraint optimization; Kernel; Large-scale systems; Machine learning; Machine learning algorithms; Statistical learning; Support vector machine classification; Support vector machines; Text categorization; Web pages;
Conference_Titel :
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2521-0
DOI :
10.1109/ICPR.2006.242
