Selective dissemination of XML documents using GAs and SVM

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.

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Abstract

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.

Item Type:	Conference Paper
Publisher:	Springer
Additional Information:	Copyright of this article belongs to Springer.
Department/Centre:	Division of Electrical Sciences > Computer Science & Automation
Date Deposited:	04 Jun 2010 10:36
Last Modified:	23 Oct 2018 08:04
URI:	http://eprints.iisc.ac.in/id/eprint/27529

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