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A feature extraction method using base phrase and keyword in Chinese text

机译:中文文本中基本短语和关键字的特征提取方法

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The feature extraction is the most key technology of text categorization. The word is used as the feature in the traditional text classification, and its effect for the text classification is evidence. The feature extraction method using base phrase and keyword changes the feature extraction of Chinese text from syntax and semantic further. In the first, analyzing the feature of baseNP and basedVP, and then make some words into baseNP and baseVP which accord to the rules of phrase, give WSD to other words in the finally. The paper proposes a stepwise feature extraction from word to phrase. The experiment results show that this method can perform much better than traditional feature extraction method, it can improve the text classification precision and recall.
机译:该特征提取是文本分类最关键的技术。该单词用作传统文本分类中的功能,其对文本分类的效果是证据。使用基本短语和关键字的特征提取方法更改了语法和语义的中文文本的特征提取。首先,分析BaseNP和基于VP的功能,然后将一些单词变为BaseNP和Basevp,符合短语规则,最终将WSD提供给其他单词。本文提出了从单词到短语的逐步特征提取。实验结果表明,该方法可以比传统的特征提取方法更好地表现得多,可以改善文本分类精度和召回。

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