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 JCC  Vol.3 No.9 , September 2015
User Preferences-Based and Time-Sensitive Location Recommendation Using Check-In Data
Abstract: Location-based social networks have attracted increasing users in recent years. Human movements and mobility patterns have a high degree of freedom and provide us with a lot of trajectory to understand the activity of users. In this paper, we present a user preferences and time sensitive recommender systems that offer an appropriate venue for a user when he appears in a special time at a particular location. The system considering the factors are: 1) the popularity of a location; 2) the preferences of a user; 3) social influence of the friends of the user and the friends who are check-in at the same location with the user; and 4) the time feature of the location and the user visiting. We evaluate our system with a large-scale real dataset from a location-based social network of Gowalla. The results confirm that our method provides more accurate location recommendations compared to the baseline.
Cite this paper: Zhang, S. , Ren, K. (2015) User Preferences-Based and Time-Sensitive Location Recommendation Using Check-In Data. Journal of Computer and Communications, 3, 18-27. doi: 10.4236/jcc.2015.39003.
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