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Personalized real-time location-tagged contents recommender system based on mobile social networks

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2 Author(s)
Hyeong-Joon Kwon ; School of Information and Communication Engineering, Sungkyunkwan University, South Korea ; Kwang-Seok Hong

This paper proposes a real-time location-tagged contents recommender system which is based on mobile social network. The system locates a user via global positioning system, and then applies distance and preference filtering methods. We confirmed that the system is highly effective and applicable to convergence by a location data and content recommender through an implementation and preference prediction experiments.

Published in:

2012 IEEE International Conference on Consumer Electronics (ICCE)

Date of Conference:

13-16 Jan. 2012