Support Vector Machines Based on a Semantic Kernel for Text Categorization
نویسندگان
چکیده
We propose to solve a text categorization task using a new metric between documents, based on a priori semantic knowledge about words. This metric can be incorporated into the definition of radial basis kernels of Support Vector Machines or directly used in a K-nearest neighbors algorithm. Both SVM and KNN are tested and compared on the 20 newsgroups database. Support Vector Machines provide the best accuracy on test data.
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تاریخ انتشار 2000