Recommendations based on Social Relationships in Mobile Services
Article first published online: 9 APR 2014
Copyright © 2014 John Wiley & Sons, Ltd.
Systems Research and Behavioral Science
Special Issue: Systems Science Methods in Industrial Sectors
Volume 31, Issue 3, pages 424–436, May/June 2014
How to Cite
Qi, J., Zhu, C. and Yang, Y. (2014), Recommendations based on Social Relationships in Mobile Services. Syst. Res., 31: 424–436. doi: 10.1002/sres.2279
- Issue published online: 26 MAY 2014
- Article first published online: 9 APR 2014
- recommendation systems;
- mobile services;
- social relationships;
- filling method
The scarcity problem in user–product matrix has become severe, which is affecting the recommendation system efficiency in mobile services; it is also related to social networks and Internet of Things, where huge amount of data and complex relationships exist. This paper proposes a novel recommendation approach based on social relationships between users to handle the scarcity problem and facilitate recommendations in mobile services. We define a model of social relationships based on a set of call detail record factors of telecom users and design a vacancy-filling method to reduce the scarcity of the user–product matrix. An integrated similarity measure is provided to improve the filtering rules of neighbours of the target user. Then, we build a new recommendation system based on social relationships, with mobile services in the telecom industry as the application. Furthermore, we conductexperiments with the real-world data of voice calls, and experimental results show that the filling method proposed can effectively reduce the scarcity of the user–product matrix and our social relationships approach outperforms the collaborative filtering in terms of the call, precision and mean absolute error indicators. Copyright © 2014 John Wiley & Sons, Ltd.