Selective dissemination of XML documents using GAs and SVM


Autoria(s): Srinivasa, KG; Sharath, S; Venugopal, KR; Patnaik, Lalit M
Data(s)

2005

Resumo

XML has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Self Adaptive Migration Model Genetic Algorithm (SAMCA)[5] and multi class Support Vector Machine (SVM) are used to learn a user model. Based on the feedback from the users the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

Formato

application/pdf

Identificador

http://eprints.iisc.ernet.in/27529/1/selectve.pdf

Srinivasa, KG and Sharath, S and Venugopal, KR and Patnaik, Lalit M (2005) Selective dissemination of XML documents using GAs and SVM. In: International Conference on Computational Intelligence and Security, DEC 15-19, 2005, Xi'an.

Publicador

Springer

Relação

http://www.springerlink.com/content/d674531672802178/

http://eprints.iisc.ernet.in/27529/

Palavras-Chave #Others
Tipo

Conference Paper

PeerReviewed