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- W397572272 abstract "Feature dimension reduction is an important step in text categorization, but traditional feature dimension reduction method ignores semantic information of features. In order to solve this problem, this paper, with the semantic dictionary, proposes a new feature dimensionality reduction processing method. The word-semantic knowledge base is constructed on the basis of HowNet and The Semantic Knowledge-base of Contemporary Chinese. By using the knowledge base and the feature extraction method, text feature is mapped to semantic feature and the dimensional reduction of feature space is realized. Naive Bayes method is introduced to verify the categorization performance. The experimental results indicate that the proposed approach has a good performance of high dimension reduction and categorization." @default.
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- W397572272 date "2013-01-01" @default.
- W397572272 modified "2023-09-23" @default.
- W397572272 title "Chinese Text Feature Dimension Reduction Based on Semantics" @default.
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- W397572272 doi "https://doi.org/10.1007/978-3-642-45185-0_42" @default.
- W397572272 hasPublicationYear "2013" @default.
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