Online POI Recommendation: Learning Dynamic Geo-Human Interactions in Streams. (arXiv:2201.10983v2 [cs.IR] UPDATED)

In this paper, we focus on the problem of modeling dynamic geo-human
interactions in streams for online POI recommendations. Specifically, we
formulate the in-stream geo-human interaction modeling problem into a novel
deep interactive reinforcement learning framework, where an agent is a
recommender and an action is a next POI to visit. We uniquely model the
reinforcement learning environment as a joint and connected composition of
users and geospatial contexts (POIs, POI categories, functional zones). An
event that a user visits …

arxiv human human interactions interactions learning recommendation