Analysis of Profile Convergence in Personalized Document Retrieval Systems

Modeling user interests in personalized document retrieval system is currently a very important task. The system should gather information about the user to recommend him better results. In this paper a mathematical model of user preference and profile is considered. The main assumption is that the system does not know the preference. The main aim of the system is to build a profile close to user preference based on observations of user activities. The method for building and updating user profile is presented and a model of simulation user behaviour in such system is proposed. The analytical properties of this method are considered and two theorems are presented and proved.

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