An overview of advanced deep graph node clustering
Graph data have become increasingly important, and graph node clustering has emerged
as a fundamental task in data analysis. In recent years, graph node clustering has gradually …
as a fundamental task in data analysis. In recent years, graph node clustering has gradually …
Multi-dimensional graph neural network for sequential recommendation
Graph neural networks (GNNs) technology has been widely used in recommendation
systems because most information in recommendation systems has a graph structure in …
systems because most information in recommendation systems has a graph structure in …
Transition information enhanced disentangled graph neural networks for session-based recommendation
Session-based recommendation (SBR) is a practical task that predicts the next item based
on an anonymous behavior sequence. Most of current methods employ graph neural …
on an anonymous behavior sequence. Most of current methods employ graph neural …
Robust Stochastic Graph Generator for Counterfactual Explanations
Counterfactual Explanation (CE) techniques have garnered attention as a means to provide
insights to the users engaging with AI systems. While extensively researched in domains …
insights to the users engaging with AI systems. While extensively researched in domains …
A Graph Convolutional Network for Session Recommendation Model Based on Improved Transformer
X Zhang, T Wang - IEEE Access, 2023 - ieeexplore.ieee.org
Graph convolutional networks are widely used for session-based recommendation (SBR) of
products, aimed at solving anonymous sequence recommendation problems. However …
products, aimed at solving anonymous sequence recommendation problems. However …
Practical near-data-processing architecture for large-scale distributed graph neural network
Graph Neural Networks have drawn tremendous attention in the past few years due to their
convincing performance and high interpretability in various graph-based tasks like link …
convincing performance and high interpretability in various graph-based tasks like link …
Online content-based sequential recommendation considering multimodal contrastive representation and dynamic preferences
Y Lu, Y Duan - Neural Computing and Applications, 2024 - Springer
The online content, including live streaming and short videos, provides abundant visual and
textual product information to users, which offers insights into users' multiple and …
textual product information to users, which offers insights into users' multiple and …
Fashion Recommendation with a real Recommender System Flow
In this technical report, we present our solution of RecSys Challenge 2022 focusing on the
fashion recommendation. We produce recommendations in two steps:(i) the retrieval step …
fashion recommendation. We produce recommendations in two steps:(i) the retrieval step …
Revisiting CounteRGAN for Counterfactual Explainability of Graphs
Counterfactual explainability (CE) has been widely explored in various domains ranging
from medical image diagnosis to self-driving cars. Graph CE (GCE), on the other hand, and …
from medical image diagnosis to self-driving cars. Graph CE (GCE), on the other hand, and …
Schatten Graph Neural Networks
Y Liu, Y Chen, G Chen, J Zhang - IEEE Access, 2022 - ieeexplore.ieee.org
Graph Neural Networks (GNNs) have been intensively studied in recent years because of
their promising performance over graph-structural data and have provided assistance in …
their promising performance over graph-structural data and have provided assistance in …