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- W2359281125 abstract "The traditional text categorization method based on vector space model has to process all the documents beforehand, and some useful information would be lost. A novel support vector machine SVM-based text categorization method with discrete kernel is proposed to overcome this problem. The discrete kernel is constructed according to the character sequence of compared documents directly in the novel SVM, with the new discrete kernel then applied to SVM categorization method to compare the similarity of documents and improve the categorization effect. The computing time of the method is On to the length of the compared documents in the new method. Compared with the Gauss kernel and polynomial kernel method on Reuters-21578 text dataset, numerically experimental results manifest that the new method is efficient and effective." @default.
- W2359281125 created "2016-06-24" @default.
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- W2359281125 date "2005-01-01" @default.
- W2359281125 modified "2023-09-23" @default.
- W2359281125 title "Automatic text categorization with discrete kernel-based support vector machine" @default.
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