Research of Web-Page Multi-Class Classification System Based on Support Vector Machine

Abstract:

A Chinese web-page classification algorithm based on SVM including the important aspects of text preprocessing, feature selection and multiple-Classification algorithm. In this paper, based on the analyses of features of Web documents, this paper does research the approach of classification in Support Vector Machine (SVM) and select of Kernel function. Furthermore, a web-page classification model and algorithm that is based on Binary Tree SVM is presented. The experiments show that it not only reduces the size of train set, but also has very high training efficiency. Its precision and recall are better.

• Periodical: Applied Mechanics and Materials (Volumes 713-715)
• Pages: 2312-2316
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.713-715.2312
• Online since: January 2015
• Authors: Feng Chen*, Rong Chen, Gen Cheng Wang
• Keywords: Binary Tree Support Vector Machine (BSVM), Multi-Classification, Support Vector Machine (SVM), Webpage

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