Cooperative Community Selection in Multi Agent Filtering Framework

  • Authors:
  • Sahin Albayrak;Dragan Milosevic

  • Affiliations:
  • DAI-Lab, Technical University Berlin, Germany;DAI-Lab, Technical University Berlin, Germany

  • Venue:
  • IAT '05 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
  • Year:
  • 2005

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Abstract

In nowadays easy to produce and publish information society, filtering services have to be able to simultaneously search in many potentially relevant and highly dynamic distributed sources. Ignoring a necessity to address information retrieval tasks in both distributed and dynamic enough manner is a major drawback for many existed search engines which try to survive the ongoing information explosion. The essence of a proposed solution for performing distributed filtering is in both installing filtering communities around information sources and setting a comprehensive cooperation mechanism, which both takes care about the dynamics of each particular source and tries to improve itself during a runtime. The applicability of the presented cooperation among communities is illustrated in a system serving as intelligent personal information assistant (PIA). Experimental results show that integrated cooperation mechanisms manage to enlarge the average user satisfaction for more than 10% while increasing the average duration of filtering for less than 4 seconds.