International Conference
AugWard: Augmentation-Aware Representation Learning for Accurate Graph Classification
Minjun Kim,
Jaehyeon Choi,
SeungJoo Lee,
Jinhong Jung,
and U Kang
Multi-Behavior Recommender Systems: A Survey
Kyungho Kim,
Sunwoo Kim,
Geon Lee,
Jinhong Jung,
and Kijung Shin
ELiCiT: Effective and Lightweight Lossy Compression of Tensors
Jihoon Ko,
Taehyung Kwon,
Jinhong Jung,
Jun-Gi Jang,
and Kijung Shin
MuLe: Multi-Grained Graph Learning for Multi-Behavior Recommendation
Seunghan Lee,
Geonwoo Ko,
Hyun-Je Song,
and Jinhong Jung
Compact Decomposition of Irregular Tensors for Data Compression: From Sparse to Dense to High-Order Tensors
Taehyung Kwon,
Jihoon Ko,
Jinhong Jung,
Jun-Gi Jang,
and Kijung Shin
TensorCodec: Compact Lossy Compression of Tensors without Strong Data Assumptions
Taehyung Kwon,
Jihoon Ko,
Jinhong Jung,
and Kijung Shin
NeuKron: Constant-Size Lossy Compression of Sparse Reorderable Matrices and Tensors
Taehyung Kwon,
Jihoon Ko,
Jinhong Jung,
and Kijung Shin
Time-aware Random Walk Diffusion to Improve Dynamic Graph Learning
Jong-whi Lee,
and Jinhong Jung
Accurate Node Feature Estimation with Structured Variational Graph Autoencoder
Jaemin Yoo,
Hyunsik Jeon,
Jinhong Jung,
and U Kang
Learning to Walk across Time for Interpretable Temporal Knowledge Graph Completion
Jaehun Jung,
Jinhong Jung,
and U Kang
BalanSiNG: Fast and Scalable Generation of Realistic Signed Networks
Jinhong Jung,
Ha-Myung Park,
and U Kang
Zoom-SVD: Fast and Memory Efficient Method for Extracting Key Patterns in an Arbitrary Time Range
Jun-Gi Jang,
Dongjin Choi,
Jinhong Jung,
and U Kang
TPA: Fast, Scalable, and Accurate Method for Approximate Random Walk with Restart on Billion Scale Graphs
Minji Yoon,
Jinhong Jung,
and U Kang
A Comparative Study of Matrix Factorization and Random Walk with Restart in Recommender Systems
Haekyu Park,
Jinhong Jung,
and U Kang
BePI: Fast and Memory-Efficient Method for Billion-Scale Random Walk with Restart
Jinhong Jung,
Namyong Park,
Lee Sael,
and U Kang
A New Question Answering Approach with Conceptual Graph
Kyung-Min Kim,
Jinhong Jung,
Jihee Ryu,
Ha-Myung Park,
Joseph P.Joohee,
Seokwoo Jeong,
U Kang,
and Sung-Hyon Myaeng
Personalized Ranking in Signed Networks using Signed Random Walk with Restart
Jinhong Jung,
Woojeong Jin,
Lee Sael,
and U Kang
BEAR:Block Elimination Approach for Random Walk with Restart on Large Graphs
Kijung Shin,
Jinhong Jung,
Lee Sael,
and U Kang
International Journal
Domestic Conference
Signed Bipartite Graph Neural Network using Personalized Propagation
Gyeong-Min Gu,
Minseo Jeon,
Hyun-Je Song,
and Jinhong Jung
Effective Representation Learning on Hypergraphs with Personalized PageRank
Daewon Gwak,
and Jinhong Jung
Effective Sequential Recommender System with User Sentiment Feedbacks
Junwoo Jung,
Cheolhee Jung,
and Jinhong Jung
Improving Accuracy of Recommendation System through Active Recommendation
Minkyung Lee,
Jinhong Jung,
and U Kang