Time-Sensitive Multi-Dimensional Recommender in database system

In this paper, we describe our proposal for Time-Sensitive Multi-Dimensional Recommender System. Recommender system is useful tool for recommending to clients on our latest and useful devices especially smartphones. However, most of them are not perfect to all clients. Even recommender systems give recommendations to them, users are not satisfied. The reason that users are not satisfied is that recommender systems are not suggesting new interesting items to users from tremendous items instead going cycle of suggesting best items to users repeatedly. We propose our review following studies: [1, 2, 3, 4, 6]. With software application that [1] provides RecDB, we would make a prototype recommender system using knowledge of RecDB, RecATHON, Matrix and Tensor Factorizations, and time-sensitive, and real-time Recommending System. Therefore, we build prototype to satisfy users.