Ming Zhao*, Tao Liu
Journal of Information Hiding and Privacy Protection, Vol.2, No.3, pp. 125-134, 2020, DOI:10.32604/jihpp.2020.010211
- 18 December 2020
Abstract The problem of low accuracy of POI (Points of Interest)
recommendation in LBSN (Location-Based Social Networks) has not been
effectively solved. In this paper, a POI recommendation algorithm based on nonconvex regularized tensor completion is proposed. The fourth-order tensor is
constructed by using the current location category, the next location category,
time and season, the regularizer is added to the objective function of tensor
completion to prevent over-fitting and reduce the error of the model. The
proximal algorithm is used to solve the objective function, and the adaptive
momentum is introduced to improve the efficiency More >
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