中文文本分类中一种基于语义的特征降维方法 |
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引用本文: | 胡涛,刘怀亮.中文文本分类中一种基于语义的特征降维方法[J].现代情报,2011,31(11):46-50. |
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作者姓名: | 胡涛 刘怀亮 |
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作者单位: | 西安电子科技大学经济管理学院,陕西 西安710071 |
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摘 要: | 文本提出了一种基于语义的特征降维方法。通过依存关系抽取实现一次降维;通过计算类别和依存关系特征项的语义相似度,结合互信息方法进行特征选择实现二次降维。对中文文本分类的实验结果表明,提出的特征降维方法具有较好的分类效果。
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关 键 词: | 文本分类 特征降维 互信息 依存关系 语义 |
Method of Feature Reduction in Chinese Text Classification Based on Semantics |
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Authors: | Hu Tao Liu Huailiang |
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Institution: | School of Management,Xidian University,Xi'an 710071,China |
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Abstract: | This paper introduced a semantic-based feature dimension reduction method.Dependencies extracted by dimensionality reduction;by calculating the semantic similarity of categories and dependencies,combined with the multi-information feature selection method for the second dimension reduction.Experiments in Chinese text classification showed that the proposed feature dimension reduction method has better classification results. |
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Keywords: | text classification dimension reduction multi-information dependency relation semantic |
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