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Multiagentes para a Filtragem de Páginas Web

Flávia C. DelicatoLuci PirmezLuiz Fernando Rust da Costa Carmo

With the current growth of the information available in Internet, users are facing an information overload. This work proposes a multiagent system for Web pages personalized filtering. The system is composed by a set of autonomous and adaptive agents that automatically provide relevant documents to the user according to a preferences profile. The agents learn with the user feedback and attempt to produce better results over time. This work presents the system description and the promising results of tests performed in a simulated environment. The proposed system proved to be a useful tool to recommend successfully relevant information to a well-defined preferences user.

http://www.lbd.dcc.ufmg.br:8080/colecoes/sbrc/2001/033.pdf

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