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Web personalization is an approach, a marketing tool and a fine art. With the rapid development of Deep Web, a large number of web information often lead to \"Information overload\" and \"Information disorientated \", yet, personalized techniques can solve this problem. Personalized techniques are one such software tool used to help users obtain recommendations for unseen items based on their preferences. The commonly used personalized techniques are content based filtering, collaborative filtering and rule based filtering. In this paper, the authors present a survey on a personalized collaborative filtering method combining the association rule mining focusing on the problems that have been identifying and the solution that have been proposed.
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