%0 Journal Article %A ZHANG Songhui %A XIONG Hanjiang %T Point-of-Interest Recommendation Algorithm Based on Poisson Factorization and Neural Network %D 2020 %R 10.3778/j.issn.1002-8331.1909-0072 %J Computer Engineering and Applications %P 176-186 %V 56 %N 21 %X

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.

%U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.1909-0072