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An improved text feature selection method based on key words

机译:一种改进的基于关键词的文本特征选择方法

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摘要

Vector space model is commonly used in the formal representation on text, but this approach would not highlight the features which play a key role in the text contents. An improved feature selection method based on key words was proposed, which uses text structural information and mutual information theory to extract key words on text content. Through using support vector machine (SVM) classifier to test, results showed that classification accuracy has improved significantly.
机译:传染媒介空间模型通常用于文本的正式表示,但这种方法不会突出显示在文本内容中扮演关键作用的功能。提出了一种基于关键词的改进的特征选择方法,它使用文本结构信息和相互信息理论提取文本内容的关键词。通过使用支持向量机(SVM)分类器进行测试,结果表明,分类精度显着提高。

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