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SQPMF: Successive Point of Interest Recommendation System Based on Probability Matrix Factorization
  • Jie Wang
Jie Wang
Dalian Maritime University

Corresponding Author:[email protected]

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Abstract

To utilize the context information, this paper proposes a novel successive POI recommendation method, SQPMF, which integrates user personal preference, user social relationship and POI transition relationship into the system for accurate recommendation of the next POI. Our experimental evaluation using two real-life datasets, Foursquare and Gowalla, show that our method SQPMF consistently outperforms all state-of-the-art systems in recommendation of successive POIs. Compared with other methods, SQPMF improves Precision and Recall by more than 21.23% and 22.71%, respectively.