Personalized Movie Recommendation Based On Context-Aware

With the fast development of the Web 2.0, it makes much more easier to create and share the information, including photos, music and videos. The huge amount of information fulfills people’s life, however, it also makes people feel confused in front of the large scale of information. The explosion of information brings them a lot of trouble in figuring out what they really need.The search engine has become a necessary tool to seek information on the Internet, which provides a way for users to find out needed information. People use search engine to seek the specific information. However, when people have specific need, they could not find the information only by search engine. For example, if people want to watch a movie to relax, they could not make decision on search engine, Sometimes, they have to browser a lot of web sites and find out the movie. The recommender system presents a selection of items to the user best fit his or her needs, which is based on items the user has bookmarked, rated, bought, recently viewed, etc.The paper firstly introduces the background of the recommendation system, the development of recommendation technology and then proposed a context-aware based movie recommend system. In this paper, a set of user research method is used in the research to develop a context-aware user modeling. Finally, a context-aware model is built to incorporate into the recommendation system, in order to improve the user satisfaction of the movie recommendation.