Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
Collaborative interface agents
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Communications of the ACM
Methods and metrics for cold-start recommendations
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Meta-modelling in Agent Oriented Software Engineering
IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
Agent-based collaborative filtering based on fuzzy recommendations
International Journal of Web Engineering and Technology
Complex Systems and Agent-Oriented Software Engineering
Engineering Environment-Mediated Multi-Agent Systems
Managing Contradictions in Multi-Agent Systems
IEICE - Transactions on Information and Systems
Estimating costs for agent oriented software
AOSE'05 Proceedings of the 6th international conference on Agent-Oriented Software Engineering
Implementing multi-agent systems organizations with INGENIAS
ProMAS'05 Proceedings of the Third international conference on Programming Multi-Agent Systems
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This paper presents a multi-agent system (MAS) that implements a recommender system, essentially using collaborative filtering techniques. The design of the MAS is flexible to support the implementation of different filtering strategies and to control the global behavior of the system and its users. It has been applied in the PSI3 project to implement a personalized information dissemination service. Personalization requires some feedback from users in order to obtain some rating of their satisfaction with the information they receive. But, in order to make this effective, it has to be done with minimum disturbance to them. One way to achieve such purpose is by associating a personal agent for each user (to build and manage the user's profile) and a community agent for each group of users (to manage the dissemination and evaluation of information in the group, improve system performance, and prevent malicious behavior).