Text Categorization Using a Personalized, Adaptive, and Cooperative MultiAgent System

نویسندگان

  • Giancarlo Cherchi
  • Andrea Manconi
  • Eloisa Vargiu
  • Dario Deledda
چکیده

In this paper, a multiagent system for supporting users in retrieving information from heterogeneous data sources, and classifying them according to users’ personal preferences, is presented. The system is built upon PACMAS, a generic architecture that supports the implementation of Personalized, Adaptive, and Cooperative MultiAgent Systems. Preliminary tests have been conducted to evaluate the effectiveness of the system in retrieving and classifying newspaper articles. Results show an avarage accuracy of about 80%.

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تاریخ انتشار 2005