Research Of The Location-based Service Recommendation System Based On User Preference

The explosive growth of information have caused great selection problems for people. However, the recommendation system can solve the problems effectively by analyzing the users’ historical data. After the data mining, it can find out the relations between the users and the projects and meanwhile it can generate personalized recommendation service to meet their needs in complex information.With the development of network technology and the popularity of smart devices, the access of information resources can occur at any time, any place and in any way. The mobile service recommendation system has enjoyed increasingly attention. Compared with traditional recommendation systems, the mobile systems need to consider more factors like locations, situations and so on.In order to having the further study of the mobile recommendation system, this paper analyzes the current research of the personalized recommendation and compares various recommendation algorithms. The mobile recommendation system should not only take the users’ preferences into account, but also analyze the context of the users’location. To have a satisfying recommendation result, the paper proposes an algorithm based on a score of users’characteristics and consuming propensity. Finally, the system is implemented and tested in Android platform...