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Intelligent applications deliver personalized experiences and services to the user. This is done by creating and using a profile of the user: user profiling. Several approaches and algorithms are developed for user profiling. This paper describes a multi agent approach that allows multiple algorithms to be combined dynamically to generate a knowledge and interest profile of a user. IBM's ABLE environment was used for the implementation of the multi agent system. To test the system, the user interest profile is build on browse behavior and this profile is applied in a TV program recommender system. The results of implemented system show that multi agent systems provide an excellent platform for an extendible user profiling system that can use multiple classifiers.

A Multi Agent Approach to Interest Profiling of Users