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Although various Social Network Services available on the Web, there are additional requirements for sharing systematic knowledge and experiences that are formed in u-Computing environment in relation to the physical location information to support problem solutions more effectively. As the numbers of information available increases, there are more inadequate and junk information which consume efforts and time for information search and sharing. In order to support personalized social network services, there are technical and service oriented requirements for managing and providing accumulative experiences of social users according to their own knowledge and life-style. Such social network services generally implements a recommendation system that provides services based on user history and profiles including statistics information for service customization. Therefore there is probability of producing irrelevant information results because of the fact that the conventional recommendation system does not consider to support a dynamic generation of the context information of users. In order to overcome accuracy problems for the conventional recommendations, the paper proposes a personalized recommendation system using psychographics information, which explains user's lifestyle.