Srinivasa, KG and Venugopal, KR and Patnaik, LM (2007) Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines. In: Intelligent Data Analysis, 11 (5). pp. 481-496.Full text not available from this repository. (Request a copy)
Extensible Markup Language ( 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 Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is 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:||Journal Article|
|Additional Information:||copyright of this article belongs to IOS Press|
|Department/Centre:||Division of Electrical Sciences > Computer Science & Automation (Formerly, School of Automation)|
|Date Deposited:||07 Jun 2010 09:16|
|Last Modified:||07 Jun 2010 09:16|
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