Cooperative community selection in multi agent filtering framework

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.