Mutli-agent System for Personalizing Information Source Selection

This paper proposes a new approach using a multi agents system for personalizing the information source selection. Most prior research for information source selection focused on selecting the sources that has the most relevant content according to the query but ignored the user’s specific needs. Our approach extends the state of the art in distributed information retrieval. First, it develops models for representing both user and information source using feature based profiles. Second, it develops an agent called user-agent for managing the user profile. Third, it develops an agent called source-agent for each information source in order to manage its information source (source profile) in parallel. Fourth, it develops an agent called agent-broker for cooperating between user-agent and each source-agent in order to select the best source to the user’s query. The approach has been experimented with several known information sources. The experimental results obtained show that the approach: (1) Improve the relevance of the result. (2) Reduce the response times. (3) Improve the system extensibility.