An Agent Based System for Intelligent Collaborative Filtering

  • Colm O’Riordan
  • Humphrey Sorensen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1652)


This paper describes a multi-agent approach to collaborative filtering. The system combines traditional content filtering (using a semantic network representation and a spreading activation search for comparison) and social filtering (achieved via agent communication which is effectively triggered by user feedback). Collaborative relationships form between the agents as agents learn to trust or distrust other agents. The system aids users in overcoming the problem of information overload by presenting, on a daily basis, a ‘personalised newspaper’ comprising articles relevant to the user.


Semantic Network Collaborative Filter User Feedback Collaborative Relationship Trust Level 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Colm O’Riordan
    • 1
  • Humphrey Sorensen
    • 2
  1. 1.I.T. CentreNational University of IrelandGalway
  2. 2.Computer Science Dept.University College CorkIreland

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