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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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) 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|
|Additional Information:||Copyright of this article belongs to Springer.|
|Date Deposited:||04 Jun 2010 10:36|
|Last Modified:||19 Sep 2010 06:01|
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