Link prediction techniques, applications, and performance: A survey
Link prediction finds missing links (in static networks) or predicts the likelihood of future links
(in dynamic networks). The latter definition is useful in network evolution (Wang et al., 2011; …
(in dynamic networks). The latter definition is useful in network evolution (Wang et al., 2011; …
Community detection algorithms in healthcare applications: a systematic review
Over the past few years, the number and volume of data sources in healthcare databases
has grown exponentially. Analyzing these voluminous medical data is both opportunity and …
has grown exponentially. Analyzing these voluminous medical data is both opportunity and …
Gcc: Graph contrastive coding for graph neural network pre-training
Graph representation learning has emerged as a powerful technique for addressing real-
world problems. Various downstream graph learning tasks have benefited from its recent …
world problems. Various downstream graph learning tasks have benefited from its recent …
Anomaly detection on attributed networks via contrastive self-supervised learning
Anomaly detection on attributed networks attracts considerable research interests due to
wide applications of attributed networks in modeling a wide range of complex systems …
wide applications of attributed networks in modeling a wide range of complex systems …
Federated learning on non-iid graphs via structural knowledge sharing
Graph neural networks (GNNs) have shown their superiority in modeling graph data. Owing
to the advantages of federated learning, federated graph learning (FGL) enables clients to …
to the advantages of federated learning, federated graph learning (FGL) enables clients to …
Identification of environmental factors that promote intestinal inflammation
Genome-wide association studies have identified risk loci linked to inflammatory bowel
disease (IBD)—a complex chronic inflammatory disorder of the gastrointestinal tract. The …
disease (IBD)—a complex chronic inflammatory disorder of the gastrointestinal tract. The …
Deepinf: Social influence prediction with deep learning
Social and information networking activities such as on Facebook, Twitter, WeChat, and
Weibo have become an indispensable part of our everyday life, where we can easily access …
Weibo have become an indispensable part of our everyday life, where we can easily access …
An empirical study of graph contrastive learning
Graph Contrastive Learning (GCL) establishes a new paradigm for learning graph
representations without human annotations. Although remarkable progress has been …
representations without human annotations. Although remarkable progress has been …
Dual graph attention networks for deep latent representation of multifaceted social effects in recommender systems
Social recommendation leverages social information to solve data sparsity and cold-start
problems in traditional collaborative filtering methods. However, most existing models …
problems in traditional collaborative filtering methods. However, most existing models …