research
∙
09/03/2023
Multi-Relational Contrastive Learning for Recommendation
Personalized recommender systems play a crucial role in capturing users'...
share
research
∙
08/22/2023
How Expressive are Graph Neural Networks in Recommendation?
Graph Neural Networks (GNNs) have demonstrated superior performance on v...
research
∙
08/10/2023
SSLRec: A Self-Supervised Learning Library for Recommendation
Self-supervised learning (SSL) has gained significant interest in recent...
research
∙
07/06/2023
Knowledge Graph Self-Supervised Rationalization for Recommendation
In this paper, we introduce a new self-supervised rationalization method...
research
∙
06/19/2023
Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation
Spatial-temporal graph learning has emerged as a promising solution for ...
research
∙
06/04/2023
Graph Transformer for Recommendation
This paper presents a novel approach to representation learning in recom...
research
∙
05/22/2023
Denoised Self-Augmented Learning for Social Recommendation
Social recommendation is gaining increasing attention in various online ...
research
∙
05/18/2023
Adaptive Graph Contrastive Learning for Recommendation
Recently, graph neural networks (GNNs) have been successfully applied to...
research
∙
05/08/2023
Graph Masked Autoencoder for Sequential Recommendation
While some powerful neural network architectures (e.g., Transformer, Gra...
research
∙
05/04/2023
Disentangled Contrastive Collaborative Filtering
Recent studies show that graph neural networks (GNNs) are prevalent to m...
research
∙
03/21/2023
Debiased Contrastive Learning for Sequential Recommendation
Current sequential recommender systems are proposed to tackle the dynami...
research
∙
03/15/2023
Graph-less Collaborative Filtering
Graph neural networks (GNNs) have shown the power in representation lear...
research
∙
03/14/2023
Disentangled Graph Social Recommendation
Social recommender systems have drawn a lot of attention in many online ...
research
∙
03/14/2023
Automated Self-Supervised Learning for Recommendation
Graph neural networks (GNNs) have emerged as the state-of-the-art paradi...
research
∙
03/02/2023
Heterogeneous Graph Contrastive Learning for Recommendation
Graph Neural Networks (GNNs) have become powerful tools in modeling grap...
research
∙
02/21/2023
Multi-Modal Self-Supervised Learning for Recommendation
The online emergence of multi-modal sharing platforms (eg, TikTok, Youtu...
research
∙
02/17/2023
Multi-Behavior Graph Neural Networks for Recommender System
Recommender systems have been demonstrated to be effective to meet user'...
research
∙
02/16/2023
LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation
Graph neural network (GNN) is a powerful learning approach for graph-bas...
research
∙
07/28/2022
Self-Supervised Hypergraph Transformer for Recommender Systems
Graph Neural Networks (GNNs) have been shown as promising solutions for ...
research
∙
07/12/2022
Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation
Learning dynamic user preference has become an increasingly important co...
research
∙
06/06/2022
Multi-Behavior Sequential Recommendation with Temporal Graph Transformer
Modeling time-evolving preferences of users with their sequential item i...
research
∙
05/02/2022
Knowledge Graph Contrastive Learning for Recommendation
Knowledge Graphs (KGs) have been utilized as useful side information to ...
research
∙
04/26/2022
Hypergraph Contrastive Collaborative Filtering
Collaborative Filtering (CF) has emerged as fundamental paradigms for pa...
research
∙
04/18/2022
Spatial-Temporal Hypergraph Self-Supervised Learning for Crime Prediction
Crime has become a major concern in many cities, which calls for the ris...
research
∙
02/17/2022
Contrastive Meta Learning with Behavior Multiplicity for Recommendation
A well-informed recommendation framework could not only help users ident...
research
∙
01/07/2022
Spatial-Temporal Sequential Hypergraph Network for Crime Prediction
Crime prediction is crucial for public safety and resource optimization,...
research
∙
01/07/2022
Multi-Behavior Enhanced Recommendation with Cross-Interaction Collaborative Relation Modeling
Many previous studies aim to augment collaborative filtering with deep n...
research
∙
10/08/2021
Global Context Enhanced Social Recommendation with Hierarchical Graph Neural Networks
Social recommendation which aims to leverage social connections among us...
research
∙
10/08/2021
Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network
Accurate forecasting of citywide traffic flow has been playing critical ...
research
∙
10/08/2021
Multiplex Behavioral Relation Learning for Recommendation via Memory Augmented Transformer Network
Capturing users' precise preferences is of great importance in various r...
research
∙
10/08/2021
Knowledge-Enhanced Hierarchical Graph Transformer Network for Multi-Behavior Recommendation
Accurate user and item embedding learning is crucial for modern recommen...
research
∙
10/08/2021
Graph-Enhanced Multi-Task Learning of Multi-Level Transition Dynamics for Session-based Recommendation
Session-based recommendation plays a central role in a wide spectrum of ...
research
∙
10/08/2021
Knowledge-aware Coupled Graph Neural Network for Social Recommendation
Social recommendation task aims to predict users' preferences over items...
research
∙
10/08/2021
Graph Meta Network for Multi-Behavior Recommendation
Modern recommender systems often embed users and items into low-dimensio...
research
∙
10/08/2021