Yeon-Chang Lee

Computer Science · Physical Sciences

14h-index702citations56works9.52yr avg
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Research Topics

Advanced Graph Neural Networks(27), Recommender Systems and Techniques(21), Complex Network Analysis Techniques(11), Topic Modeling(10), Caching and Content Delivery(6)

Publications56 total

Echoes in the Loop: Diagnosing Risks in LLM-Powered Recommender Systems under Feedback Loops
arXiv (Cornell University)·2026Open Access
Echoes in the Loop: Diagnosing Risks in LLM-Powered Recommender Systems under Feedback Loops
arXiv (Cornell University)·2026Open Access
Improving the Accuracy of Community Detection on Signed Networks via Community Refinement and Contrastive Learning
arXiv (Cornell University)·2026Open Access
Improving the Accuracy of Community Detection on Signed Networks via Community Refinement and Contrastive Learning
ArXiv.org·2026Open Access
Disentangling, Amplifying, and Debiasing: Learning Disentangled Representations for Fair Graph Neural Networks
Proceedings of the AAAI Conference on Artificial Intelligence·2025Open Access
CAPER: Enhancing Career Trajectory Prediction using Temporal Knowledge Graph and Ternary Relationship
2025· 1 citedOpen Access
CATER: A Cluster-Based Alternative-Term Recommendation Framework for Large-Scale Web Search at NAVER
2025
Uncovering High-Order Cohesive Structures: Efficient (K,G)-Core Computation and Decomposition for Large Hypergraphs
SSRN Electronic Journal·2025Open Access
<scp>PolarDSN</scp> : An Inductive Approach to Learning the Evolution of Network Polarization in Dynamic Signed Networks
2024· 1 cited
Towards Fair Graph Anomaly Detection: Problem, Benchmark Datasets, and Evaluation
2024· 1 citedOpen Access
A Survey on the Role of Crowds in Combating Online Misinformation: Annotators, Evaluators, and Creators
ACM Transactions on Knowledge Discovery from Data·2024· 9 cited
CAPER: Enhancing Career Trajectory Prediction using Temporal Knowledge Graph and Ternary Relationship
arXiv (Cornell University)·2024· 2 citedOpen Access
Disentangling, Amplifying, and Debiasing: Learning Disentangled Representations for Fair Graph Neural Networks
arXiv (Cornell University)·2024Open Access
Trustworthiness-Driven Graph Convolutional Networks for Signed Network Embedding
ACM Transactions on Knowledge Discovery from Data·2024· 1 cited
Deep Opinion-Unaware Blind Image Quality Assessment by Learning and Adapting from Multiple Annotators
2024· 5 citedOpen Access
Empowering Interdisciplinary Insights with Dynamic Graph Embedding Trajectories
arXiv (Cornell University)·2024Open Access
SVD-AE: Simple Autoencoders for Collaborative Filtering
arXiv (Cornell University)·2024Open Access
A Survey of Graph Neural Networks for Social Recommender Systems
ACM Computing Surveys·2024· 160 citedOpen Access
Towards Fair Graph Anomaly Detection: Problem, Benchmark Datasets, and Evaluation
arXiv (Cornell University)·2024· 1 citedOpen Access
Learning to compensate for lack of information: Extracting latent knowledge for effective temporal knowledge graph completion
Information Sciences·2023· 10 cited
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Frequent Co-authors

Sang‐Wook Kim(37), Srijan Kumar(9), Dongwon Lee(7), Kyungsik Han(5), Kartik Sharma(4), Jeongwhan Choi(4), Noseong Park(4), Taeho Kim(4), JaeHyun Lee(4), Taeri Kim(3), Kijung Shin(3), Yiqiao Jin(3), M. J. Kim(3), Jiwon Hong(3), Sivagami Nambi(2), Aditya Salian(2), Shlok Shah(2), Jongwuk Lee(2), Taeyong Kong(2), Jinsung Jeon(2)