GETNext: trajectory flow map enhanced transformer for next POI recommendation
Next POI recommendation intends to forecast users' immediate future movements given their
current status and historical information, yielding great values for both users and service …
current status and historical information, yielding great values for both users and service …
ReFRS: Resource-efficient federated recommender system for dynamic and diversified user preferences
Owing to its nature of scalability and privacy by design, federated learning (FL) has received
increasing interest in decentralized deep learning. FL has also facilitated recent research on …
increasing interest in decentralized deep learning. FL has also facilitated recent research on …
Graph-enhanced spatial-temporal network for next POI recommendation
The task of next Point-of-Interest (POI) recommendation aims at recommending a list of POIs
for a user to visit at the next timestamp based on his/her previous interactions, which is …
for a user to visit at the next timestamp based on his/her previous interactions, which is …
Privacy-preserving point-of-interest recommendation based on simplified graph convolutional network for geological traveling
The provision of privacy-preserving recommendations for geological tourist attractions is an
important research area. The historical check-in data collected from location-based social …
important research area. The historical check-in data collected from location-based social …
A graph-based approach for trajectory similarity computation in spatial networks
Trajectory similarity computation is an essential operation in many applications of spatial
data analysis. In this paper, we study the problem of trajectory similarity computation over …
data analysis. In this paper, we study the problem of trajectory similarity computation over …
Spatial-temporal hypergraph self-supervised learning for crime prediction
Crime has become a major concern in many cities, which calls for the rising demand for
timely predicting citywide crime occurrence. Accurate crime prediction results are vital for the …
timely predicting citywide crime occurrence. Accurate crime prediction results are vital for the …
Learning graph-based disentangled representations for next POI recommendation
Next Point-of-Interest (POI) recommendation plays a critical role in many location-based
applications as it provides personalized suggestions on attractive destinations for users …
applications as it provides personalized suggestions on attractive destinations for users …
Decentralized collaborative learning framework for next POI recommendation
Next Point-of-Interest (POI) recommendation has become an indispensable functionality in
Location-based Social Networks (LBSNs) due to its effectiveness in helping people decide …
Location-based Social Networks (LBSNs) due to its effectiveness in helping people decide …
Hierarchical multi-task graph recurrent network for next poi recommendation
Learning which Point-of-Interest (POI) a user will visit next is a challenging task for
personalized recommender systems due to the large search space of possible POIs in the …
personalized recommender systems due to the large search space of possible POIs in the …
A survey on deep learning based Point-of-Interest (POI) recommendations
Abstract Location-based Social Networks (LBSNs) enable users to socialize with friends and
acquaintances by sharing their check-ins, opinions, photos, and reviews. A huge volume of …
acquaintances by sharing their check-ins, opinions, photos, and reviews. A huge volume of …