Graph neural networks (GNNs) have recently emerged as an effective collaborative filtering
(CF) approaches for recommender systems. The key idea of GNN-based recommender …

Next Point-of-Interest (POI) recommendation task focuses on predicting the immediate next
position a user would visit, thus providing appealing location advice. In light of this, graph …

We present the hierarchical graph infomax (HGI) approach for learning urban region
representations (vector embeddings) with points-of-interest (POIs) in a fully unsupervised …

Abstract Next Point-Of-Interest (POI) recommendation plays an important role in various
location-based services. Its main objective is to predict the user's next interested POI based …

The next Point of Interest (POI) recommendation task is to predict users' immediate next POI
visit given their historical data. Location-Based Social Network (LBSN) data, which is often …

Next Point-of-Interest (POI) recommendation is an essential part of the flourishing location-
based applications, where the demands of users are not only conditioned by their recent …

Providing potential next point-of-interest (POI) suggestions for users has become a
prominent task in location-based social networks, which receives more and more attention …

Learning the next Point-of-Interest (POI) is a highly context-dependent human movement
behavior prediction task, which has gained increasing attention with the consideration of …

Amid the rise of mobile technologies and Location-Based Social Networks (LBSNs), there's
an escalating demand for personalized Point-of-Interest (POI) recommendations. Especially …

The rapid expansion of Location-Based Social Networks (LBSNs) has highlighted the
importance of effective next Point-of-Interest (POI) recommendations, which leverage …