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IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5
Support Vector Machines Based on a Semantic Kernel for Text Categorization
Como, Italy
July 24-July 27
ISBN: 0-7695-0619-4
Georges Siolas, Universit? Pierre et Marie Curie
Florence d'Alché-Buc, Universit? Pierre et Marie Curie
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.
Citation:
Georges Siolas, Florence d'Alché-Buc, "Support Vector Machines Based on a Semantic Kernel for Text Categorization," ijcnn, vol. 5, pp.5205, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5, 2000
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