Selective Dissemination of XML Documents Using GAs and SVM

  • K. G. Srinivasa
  • S. Sharath
  • K. R. Venugopal
  • Lalit M. Patnaik
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3801)

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 (SAMGA)[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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • K. G. Srinivasa
    • 1
  • S. Sharath
    • 2
  • K. R. Venugopal
    • 1
  • Lalit M. Patnaik
    • 3
  1. 1.Department of Computer Science and EngineeringUniversity Visvesvaraya College of EngineeringBangaloreIndia
  2. 2.Infosys TechnologiesBangaloreIndia
  3. 3.Microprocessor Applications LaboratoryIndian Institute of ScienceIndia

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