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PG^2Net: Personalized and Group Preferences Guided Network for Next Place Prediction
[article]
2021
arXiv
pre-print
Predicting the next place to visit is a key in human mobility behavior modeling, which plays a significant role in various fields, such as epidemic control, urban planning, traffic management, and travel recommendation. To achieve this, one typical solution is designing modules based on RNN to capture their preferences to various locations. Although these RNN-based methods can effectively learn individual's hidden personalized preferences to her visited places, the interactions among users can
arXiv:2110.08266v1
fatcat:ea3pz4t4tvbq3aw5hahb6yydfm