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- W1878100865 abstract "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." @default.
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- W1878100865 date "2007-10-10" @default.
- W1878100865 modified "2023-09-24" @default.
- W1878100865 title "Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines" @default.
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- W1878100865 doi "https://doi.org/10.3233/ida-2007-11504" @default.
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