An Agent Based System for Intelligent Collaborative Filtering
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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.
KeywordsSemantic Network Collaborative Filter User Feedback Collaborative Relationship Trust Level
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