Support Vector Machines Based on a Semantic Kernel for Text Categorization

Como, Italy July 24-July 27

DOI Bookmark:

http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.861458

IEEE-INNS-ENNS International Joint Co ...

	This Article
	PURCHASE ARTICLE: $19 PDF HTML IEEE Xplore Subscribers
	Share
	Email this Article to a friend
	Bibliographic References
	ASCII Text BibTex RefWorks Procite/RefMan/Endnote
	Add to:
	Digg Furl Spurl Blink Simpy Google Del.icio.us Y!MyWeb
	Search
	Similar Articles Articles by Georges Siolas Articles by Florence d'Alché-Buc

	ASCII Text	x
	Georges Siolas, Florence d'Alché-Buc, "Support Vector Machines Based on a Semantic Kernel for Text Categorization," Neural Networks, IEEE - INNS - ENNS International Joint Conference on, vol. 5, pp. 5205, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5, 2000.

	BibTex	x
	@article{ 10.1109/IJCNN.2000.861458, author = {Georges Siolas and Florence d'Alché-Buc}, title = {Support Vector Machines Based on a Semantic Kernel for Text Categorization}, journal ={Neural Networks, IEEE - INNS - ENNS International Joint Conference on}, volume = {5}, year = {2000}, issn = {1098-7576}, pages = {5205}, doi = {http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.861458}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Neural Networks, IEEE - INNS - ENNS International Joint Conference on TI - Support Vector Machines Based on a Semantic Kernel for Text Categorization SN - 1098-7576 SP EP A1 - Georges Siolas, A1 - Florence d'Alché-Buc, PY - 2000 VL - 5 JA - Neural Networks, IEEE - INNS - ENNS International Joint Conference on ER -

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

Peer Review Notice | Give Us Feedback

Usage of this product signifies your acceptance of the Terms of Use.