Text Classification with Support Vector Machine and Back Propagation Neural Network

Authors:
Wen Zhang;Xijin Tang;Taketoshi Yoshida
Affiliations:
School of Knowledge Science, Japan Advanced Institute of Science and Technology, 1-1 Ashahidai, Tatsunokuchi, Ishikawa 923-1292, Japan;Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, P.R. China;School of Knowledge Science, Japan Advanced Institute of Science and Technology, 1-1 Ashahidai, Tatsunokuchi, Ishikawa 923-1292, Japan
Venue:
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007
Year:
2007

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Abstract

We compared a support vector machine (SVM) with a back propagation neural network (BPNN) for the task of text classification of XiangShan science conference (XSSC) web documents. We made a comparison on the performances of the multi-class classification of these two learning methods. The result of an experiment demonstrated that SVM substantially outperformed the one by BPNN in prediction accuracy and recall. Furthermore, the result of classification was improved with the combined method which was devised in this paper.