Research of Active Recommendation Method Based on Users’ Static and Dynamic Characteristics
Yuan Jing He, Wan Lin Gao, Kun Wang, Guan Wang · Applied Mechanics and Materials · 2012
The means of active recommendation is now increasingly applied to many different domains as it might meet users’ growing demands of personalized information service in process of selective purchasing for products, and research of recommendation technology based on user’s characteristics has been a key role in study area of active recommendation. However, investigations were performed to view there are still some deficiencies on existing methods. Therefore, an active recommendation method based on users’ static and dynamic characteristics is present and this paper proceeds as following. Firstly, feature model of user interests is constructed by analyzing static and dynamic data of target users for specific recommend. After that, neighbor users who have similar attributes with object user are found by reference to user model. Last, preference of intended user for other resources is reasonably predetermined by calculating interestingness with combination of neighbors, finally in this way can the main theory basis of recommendation comes into being. So in this paper a new approach based on users’ characteristics is provided, and it is shown with this method can effectively solve problem of shortage of satisfaction of traditional recommendation.