The widespread of applications like e-commerce and recommendation systems requires the use of efficient customization techniques and user preferences handling. In database community a lot of research on this topic has been focused on extending standard SQL with preference facilities in order to provide personalized query answering. More specifically, user preferences are an essential ingredient of personalized database applications. In this paper, we consider the conditional preference queries (cp-queries) of CPrefSQL query language where user preferences are specified by a set of conditional rules. We propose new algorithms based on a technique we called preference partition that outperform the state-of-the-art algorithms for CPrefSQL preference operators significantly decreasing the number of scans over database.

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