基于SVM文本分类中的关键词学习研究

Study on Keyword Learning in SVM-based Text Classification

文本分类中分类方法与关键词是两个重要的因素,支持向量机作为一种良好的分类方法,在文本分类中表现出很好的性能。本文以支持向量机为基础,重点研究其分类过程中关键词的学习问题,在其增量分类中,同步进行关键词的增量学习调整,实验结果表明,该方法可以更好地提高文本分类的分类性能。

For classification, the classification method and keyword are the two important factors. As a good classification method, SVM is of good performance based on SVM. This paper mainly explores the keyword learning during the classification. With the incremental training , the keyword is re-learned and adjusted. The experimental result shows that the new method achieves the more excellent performance.