4 citations · 9 across the 8 of their papers we have counts for
8 papers
Criteria Tell You More than Ratings: Criteria Preference-Aware Light Graph Convolution for Effective Multi-Criteria Recommendation
Jin-Duk Park, Siqing Li, Xin Cao +1
The multi-criteria (MC) recommender system, which leverages MC rating information in a wide range of e-commerce areas, is ubiquitous nowadays. Surprisingly, although graph neural n…
Centrality-Based Node Feature Augmentation for Robust Network Alignment
Jin-Duk Park, Cong Tran, Won-Yong Shin +1
Network alignment (NA) is the task of discovering node correspondences across multiple networks. Although NA methods have achieved remarkable success in a myriad of scenarios, thei…
Joint Data Deepening-and-Prefetching for Energy-Efficient Edge Learning
Sujin Kook, Won-Yong Shin, Seong-Lyun Kim +1
The vision of pervasive machine learning (ML) services can be realized by training an ML model on time using real-time data collected by internet of things (IoT) devices. To this e…
Graph Anomaly Detection with Graph Neural Networks: Current Status and Challenges
Hwan Kim, Byung Suk Lee, Won-Yong Shin +1
Graphs are used widely to model complex systems, and detecting anomalies in a graph is an important task in the analysis of complex systems. Graph anomalies are patterns in a graph…
PAGE: Prototype-Based Model-Level Explanations for Graph Neural Networks
Yong-Min Shin, Sun-Woo Kim, Won-Yong Shin
Aside from graph neural networks (GNNs) attracting significant attention as a powerful framework revolutionizing graph representation learning, there has been an increasing demand…
Grad-Align+: Empowering Gradual Network Alignment Using Attribute Augmentation
Jin-Duk Park, Cong Tran, Won-Yong Shin +1
Network alignment (NA) is the task of discovering node correspondences across different networks. Although NA methods have achieved remarkable success in a myriad of scenarios, the…
META-CODE: Community Detection via Exploratory Learning in Topologically Unknown Networks
Yu Hou, Cong Tran, Won-Yong Shin
The discovery of community structures in social networks has gained considerable attention as a fundamental problem for various network analysis tasks. However, due to privacy conc…
Edgeless-GNN: Unsupervised Representation Learning for Edgeless Nodes
Yong-Min Shin, Cong Tran, Won-Yong Shin +1
We study the problem of embedding edgeless nodes such as users who newly enter the underlying network, while using graph neural networks (GNNs) widely studied for effective represe…