Two-step recommendation based personalization for future services

Personalization has a key role to play in making a ubiquitous computing system more usable to the end user. Our goal is to provide the end user with two-step personalization services. To do this, we propose the personalized situation model consisted of user behavior and user preferences models. The former is to set up a weighted list of useful services according to user behavior patterns of current situation. The latter is to set up a weighted list of specific contents according to the service selected by a user. That is to say, two-step personalization services are consisted of service recommendation step and contents recommendation step. As a result, if user selected TV service among service categories to be recommended at the first step, it should match a user´s desired TV programs and recommend TV programs with high user preference at the second step.