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SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
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SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
STARTS: Stanford proposal for Internet meta-searching
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Learning and Revising User Profiles: The Identification ofInteresting Web Sites
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AGENTS '98 Proceedings of the second international conference on Autonomous agents
Effective retrieval with distributed collections
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
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A decision-theoretic approach to database selection in networked IR
ACM Transactions on Information Systems (TOIS)
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A reinforcement learning agent for personalized information filtering
Proceedings of the 5th international conference on Intelligent user interfaces
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A vector space model for automatic indexing
Communications of the ACM
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Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
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ACM Transactions on Information Systems (TOIS)
Personalized Web Search For Improving Retrieval Effectiveness
IEEE Transactions on Knowledge and Data Engineering
Implicit feedback for inferring user preference: a bibliography
ACM SIGIR Forum
A Multi-Agent Approach for Peer-to-Peer Based Information Retrieval System
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
Unified utility maximization framework for resource selection
Proceedings of the thirteenth ACM international conference on Information and knowledge management
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Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
User modeling for full-text federated search in peer-to-peer networks
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Letizia: an agent that assists web browsing
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Web Information Retrieval Using Particle Swarm Optimization Based Approaches
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
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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.