PVA: A Self-Adaptive Personal View Agent

  • Chien Chin Chen
  • Meng Chang Chen
  • Yeali Sun


In this paper, we present PVA, an adaptive personal view information agent system for tracking, learning and managing user interests in Internet documents. PVA consists of three parts: a proxy, personal view constructor, and personal view maintainer. The proxy logs the user's activities and extracts the user's interests without user intervention. The personal view constructor mines user interests and maps them to a class hierarchy (i.e., personal view). The personal view maintainer synchronizes user interests and the personal view periodically. When user interests change, in PVA, not only the contents, but also the structure of the user profile are modified to adapt to the changes. In addition, PVA considers the aging problem of user interests. The experimental results show that modulating the structure of the user profile increases the accuracy of a personalization system.

machine learning automatic classification personalization agent WWW 


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Copyright information

© Kluwer Academic Publishers 2002

Authors and Affiliations

  • Chien Chin Chen
    • 1
  • Meng Chang Chen
    • 1
  • Yeali Sun
    • 2
  1. 1.Institute of Information ScienceAcademia SinicaTaiwan
  2. 2.Department of Information ManagementNational Taiwan UniversityTaiwan

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