A survey of graph neural networks for recommender systems: Challenges, methods, and directions
Recommender system is one of the most important information services on today's Internet.
Recently, graph neural networks have become the new state-of-the-art approach to …
Recently, graph neural networks have become the new state-of-the-art approach to …
Graph neural networks in recommender systems: a survey
With the explosive growth of online information, recommender systems play a key role to
alleviate such information overload. Due to the important application value of recommender …
alleviate such information overload. Due to the important application value of recommender …
Contrastive learning for representation degeneration problem in sequential recommendation
Recent advancements of sequential deep learning models such as Transformer and BERT
have significantly facilitated the sequential recommendation. However, according to our …
have significantly facilitated the sequential recommendation. However, according to our …
Predicting urban region heat via learning arrive-stay-leave behaviors of private cars
Urban region heat refers to the extent of which people congregate in various regions when
they travel to and stay in a specified place. Predicting urban region heat facilitates broad …
they travel to and stay in a specified place. Predicting urban region heat facilitates broad …
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 …
Graph-flashback network for next location recommendation
Next Point-of Interest (POI) recommendation plays an important role in location-based
applications, which aims to recommend the next POIs to users that they are most likely to …
applications, which aims to recommend the next POIs to users that they are most likely to …
Lightweight self-attentive sequential recommendation
Modern deep neural networks (DNNs) have greatly facilitated the development of sequential
recommender systems by achieving state-of-the-art recommendation performance on …
recommender systems by achieving state-of-the-art recommendation performance on …
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 …