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A wide deployment of Internet Protocol Television (IPTV), Cable Television (CATV), Internet, User Created Contents (UCC), and Digital Television (DTV) enabled the rapid increase of channels and programs which can be selected by consumers. This was not expected when we consider the conventional television program technologies and policies. Due to these paradigm changes, hundreds of channels and programs are now available to consumers. It has become difficult and time consuming to find an interesting channel and program via the remote control or channel guide map. To refine the channel selecting processes and to satisfy the consumer's requirements, we propose the Personalized DTV Program Recommendation (PDPR) system under a cloud computing environment. The proposed PDPR system analyzes and uses the viewing pattern of consumers to personalize the program recommendations, and to efficiently use computing resources.