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 …
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 …
Hierarchical adversarial attacks against graph-neural-network-based IoT network intrusion detection system
The advancement of Internet of Things (IoT) technologies leads to a wide penetration and
large-scale deployment of IoT systems across an entire city or even country. While IoT …
large-scale deployment of IoT systems across an entire city or even country. While IoT …
Atomistic line graph neural network for improved materials property predictions
K Choudhary, B DeCost - npj Computational Materials, 2021 - nature.com
Graph neural networks (GNN) have been shown to provide substantial performance
improvements for atomistic material representation and modeling compared with descriptor …
improvements for atomistic material representation and modeling compared with descriptor …
Secure artificial intelligence of things for implicit group recommendations
The emergence of Artificial Intelligence of Things (AIoT) has provided novel insights for
many social computing applications, such as group recommender systems. As the distances …
many social computing applications, such as group recommender systems. As the distances …
Deep-distributed-learning-based POI recommendation under mobile-edge networks
With the rapid development of edge intelligence in wireless communication networks,
mobile-edge networks (MENs) have been broadly discussed in academia. Supported by …
mobile-edge networks (MENs) have been broadly discussed in academia. Supported by …
Mixed graph neural network-based fake news detection for sustainable vehicular social networks
The rapid development of the Internet of Vehicles has substantially boosted the prevalence
of vehicular social networks (VSN). However, content security has gradually been a latent …
of vehicular social networks (VSN). However, content security has gradually been a latent …
Consisrec: Enhancing gnn for social recommendation via consistent neighbor aggregation
Social recommendation aims to fuse social links with user-item interactions to alleviate the
cold-start problem for rating prediction. Recent developments of Graph Neural Networks …
cold-start problem for rating prediction. Recent developments of Graph Neural Networks …
Evaluating post-hoc explanations for graph neural networks via robustness analysis
This work studies the evaluation of explaining graph neural networks (GNNs), which is
crucial to the credibility of post-hoc explainability in practical usage. Conventional evaluation …
crucial to the credibility of post-hoc explainability in practical usage. Conventional evaluation …
Deep learning-embedded social internet of things for ambiguity-aware social recommendations
Z Guo, K Yu, Y Li, G Srivastava… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
With the increasing demand of users for personalized social services, social
recommendation (SR) has been an important concern in academia. However, current …
recommendation (SR) has been an important concern in academia. However, current …