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LGLMF: Local Geographical Based Logistic Matrix Factorization Model for POI Recommendation

  • Hossein A. RahmaniEmail author
  • Mohammad Aliannejadi
  • Sajad Ahmadian
  • Mitra Baratchi
  • Mohsen Afsharchi
  • Fabio Crestani
Conference paper
  • 48 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12004)

Abstract

With the rapid growth of Location-Based Social Networks, personalized Points of Interest (POIs) recommendation has become a critical task to help users explore their surroundings. Due to the scarcity of check-in data, the availability of geographical information offers an opportunity to improve the accuracy of POI recommendation. Moreover, matrix factorization methods provide effective models which can be used in POI recommendation. However, there are two main challenges which should be addressed to improve the performance of POI recommendation methods. First, leveraging geographical information to capture both the user’s personal, geographic profile and a location’s geographic popularity. Second, incorporating the geographical model into the matrix factorization approaches. To address these problems, a POI recommendation method is proposed in this paper based on a Local Geographical Model, which considers both users’ and locations’ points of view. To this end, an effective geographical model is proposed by considering the user’s main region of activity and the relevance of each location within that region. Then, the proposed local geographical model is fused into the Logistic Matrix Factorization to improve the accuracy of POI recommendation. Experimental results on two well-known datasets demonstrate that the proposed approach outperforms other state-of-the-art POI recommendation methods.

Keywords

Point-of-Interest Contextual information Recommender systems Location-Based Social Networks 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Hossein A. Rahmani
    • 1
    Email author
  • Mohammad Aliannejadi
    • 2
  • Sajad Ahmadian
    • 3
  • Mitra Baratchi
    • 4
  • Mohsen Afsharchi
    • 1
  • Fabio Crestani
    • 2
  1. 1.University of ZanjanZanjanIran
  2. 2.Università della Svizzera ItalianaLuganoSwitzerland
  3. 3.Kermanshah University of TechnologyKermanshahIran
  4. 4.Leiden UniversityLeidenThe Netherlands

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