An optimized collaborative filtering method to construct spatial‐temporal behavior pattern‐based user interest model

Abstract

Mobile social network (MSN) has properties of real time, mobility, and social relationship, and provides more real‐time, more dimensional, and more heterogeneous metadata. The traditional user interest models represent mobile users' interests unsatisfactorily because of these inherent characteristics. This paper aims to combine the characteristics of mobile social networks appropriately to build a user interest model effectively for representing user interests. The constructed model is supposed to enable users to filter uninterested information, to provide personalized mobile service, to solve information overload, and to gain a good user experience. In order to realize these, first, we explore various issues of the traditional user interest model, and analyze the numerous problems in using traditional models to represent mobile user interests. Then a user spatial‐temporal behavior pattern in conjunction with mobile personalization attributes and context information is proposed, which is followed by a proposal of a user interest model to represent user interests. Second, we introduce a hybrid collaborative filtering method based on users and subjects to calculate user interests and to build the user interest model, considering the user interest extensive degree, the subject popularity, as well as the user influence. Finally, a model construction algorithm is proposed based on the user's spatial‐temporal behavior pattern. Experimental results show that the proposed model can represent user interests effectively under the mobile social network. Furthermore, it is verified that the adaptability and accuracy of the construction algorithm are significantly improved by considering the user interest extensive degree, the subject popularity, and the user influence. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.