STELLAR: Spatial-Temporal Latent Ranking for Successive Point-of-Interest Recommendation

  title={STELLAR: Spatial-Temporal Latent Ranking for Successive Point-of-Interest Recommendation},
  author={Shenglin Zhao and Tong Zhao and Haiqin Yang and Michael R. Lyu and Irwin King},
Successive point-of-interest (POI) recommendation in location-based social networks (LBSNs) becomes a significant task since it helps users to navigate a number of candidate POIs and provides the best POI recommendations based on users’ most recent check-in knowledge. However, all existing methods for successive POI recommendation only focus on modeling the correlation between POIs based on users’ check-in sequences, but ignore an important fact that successive POI recommendation is a time… CONTINUE READING
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Personalized Sequential Check-in Prediction: Beyond Geographical and Temporal Contexts

2018 IEEE International Conference on Multimedia and Expo (ICME) • 2018
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