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Nowadays, recommendation systems are definitely a necessity in the websites not just an auxiliary feature, especially for commercial websites and web sites with large information services. Recommendation systems use models constructed by applying statistical and data mining approaches on derived data from websites. In this paper we propose a new hybrid approach that leverages usage data and data domain of website to construct a recommendation model. A data mining model will be created by applying clustering algorithm, and then the model is adjusted by statistical approach based on the change of behavior of users or data domain of website periodically. We believe that by this novel approach the problem of inaccuracy of conventional usage data models partly due to slowly change of behavior of users or data domain of websites will be solved.