Deep learning with graph convolutional networks: An overview and latest applications in computational intelligence

UA Bhatti, H Tang, G Wu, S Marjan… - International Journal of …, 2023 - Wiley Online Library
Convolutional neural networks (CNNs) have received widespread attention due to their
powerful modeling capabilities and have been successfully applied in natural language …

Explainable graph wavelet denoising network for intelligent fault diagnosis

T Li, C Sun, S Li, Z Wang, X Chen… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Deep learning (DL)-based intelligent fault diagnosis methods have greatly promoted the
development of the field of fault diagnosis due to their powerful feature extraction ability for …

A deep learning based trust-and tag-aware recommender system

S Ahmadian, M Ahmadian, M Jalili - Neurocomputing, 2022 - Elsevier
Recommender systems are popular tools used in many applications, such as e-commerce, e-
learning, and social networks to help users select their desired items. Collaborative filtering …

Aspect-based sentiment analysis via multitask learning for online reviews

G Zhao, Y Luo, Q Chen, X Qian - Knowledge-Based Systems, 2023 - Elsevier
Aspect based sentiment analysis (ABSA) aims to identify aspect terms in online reviews and
predict their corresponding sentiment polarity. Sentiment analysis poses a challenging fine …

Generative label fused network for image–text matching

G Zhao, C Zhang, H Shang, Y Wang, L Zhu… - Knowledge-Based …, 2023 - Elsevier
Although there is a long line of research on bidirectional image–text matching, the problem
remains a challenge due to the well-known semantic gap between visual and textual …

[HTML][HTML] Agent-based recommendation in E-learning environment using knowledge discovery and machine learning approaches

Z Shahbazi, YC Byun - Mathematics, 2022 - mdpi.com
E-learning is a popular area in terms of learning from social media websites in various terms
and contents for every group of people in this world with different knowledge backgrounds …

Deep multi-graph neural networks with attention fusion for recommendation

Y Song, H Ye, M Li, F Cao - Expert Systems with Applications, 2022 - Elsevier
Graph neural networks (GNNs), with their promising potential to learn effective graph
representation, have been widely used for recommender systems, in which the given graph …

Category-aware multi-relation heterogeneous graph neural networks for session-based recommendation

H Xu, B Yang, X Liu, W Fan, Q Li - Knowledge-Based Systems, 2022 - Elsevier
Session-based recommendation (SBR) is one of the hot research areas in recent years.
Various SBR models have been proposed, of which graph neural network (GNN)-based …

Dynamic graph representation learning with neural networks: A survey

L Yang, C Chatelain, S Adam - IEEE Access, 2024 - ieeexplore.ieee.org
In recent years, Dynamic Graph (DG) representations have been increasingly used for
modeling dynamic systems due to their ability to integrate both topological and temporal …

A time-aware self-attention based neural network model for sequential recommendation

Y Zhang, B Yang, H Liu, D Li - Applied Soft Computing, 2023 - Elsevier
Sequential recommendation is one of the hot research topics in recent years. Various
sequential recommendation models have been proposed, of which Self-Attention (SA) …