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

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

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.

Kwang-Seok Hong | Hyeong-Joon Kwon | Hyeong-Joon Kwon | Kwang-seok Hong

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