Computer Engineering and Applications ›› 2020, Vol. 56 ›› Issue (21): 176-186.DOI: 10.3778/j.issn.1002-8331.1909-0072

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Point-of-Interest Recommendation Algorithm Based on Poisson Factorization and Neural Network

ZHANG Songhui, XIONG Hanjiang   

  1. 1.School of Computer, Wuhan Vocational College of Software and Engineering, Wuhan 430205, China
    2.State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
  • Online:2020-11-01 Published:2020-11-03



  1. 1.武汉软件工程职业学院 计算机学院,武汉 430205
    2.武汉大学 测绘遥感信息工程国家重点实验室,武汉 430079


The implicit feedback modeling user-Point-of-Interest(POI)interaction accuracy of the POI recommendation system is not high and the implicit feedback attribute of the use’s check-in data is ignored. A novel POI recommendation algorithm is proposed. Specifically, first of all, a neural network-based ranking algorithm is used to capture the interaction relationship of user-POI. Then, the Poisson factorization algorithm and Bayesian personalized ranking technology are combined to model the user’s check-in behavior. The algorithms obtained in the above two steps are integrated into a unified recommendation algorithm architecture to provide a POI recommendation service. The experimental results show that the proposed algorithm is better than the traditional state-of-the-art POI recommendation algorithm.

Key words: Point-of-Interest(POI) recommendation, Poisson factorization, neural network, Bayesian personalized ranking



关键词: 兴趣点推荐, 泊松分解, 神经网络, 贝叶斯个性化排序