A Java-based approach to active collaborative filtering

In this paper, we present an collaborative filtering approach to webpage filtering. The system supports users in exchanging recommendations and exploits the social relation between recommenders and recipients of recommendations instead of computing a degree of interest. In order to help users estimate the potential interestingness of a recommended webpage, the system augments the recommendation object with additional data indicating how previous recipients of the recommendation have dealt with the corresponding webpage.The system has been implemented as a collection of personal user agents exchanging recommendations with a central recommendation server. The user agents are implemented as Java applets and the recommendation server is a Java remote object realized as object factory.