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A method of Chinese text categorization based on proximal support vector machine

机译:基于近邻支持向量机的中文文本分类方法

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A Chinese text categorization method based on proximal support vector machine and similarity of words is studied in the paper. Firstly feature vectors are extracted, and then the text feature subset based on similarity of words is obtained, finally the text is categorized based on proximal support vector machine. The tests on the large-scale text show that the recall is comparatively low and the precision is comparatively high.
机译:本文研究了一种基于近邻支持向量机和词相似度的中文文本分类方法。首先提取特征向量,然后获得基于词相似度的文本特征子集,最后基于近邻支持向量机对文本进行分类。大规模文本测试表明,召回率较低,精度较高。

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