International Publications
ELiCiT: Effective and Lightweight Lossy Compression of Tensors
Jihoon Ko,
Taehyung Kwon,
Jinhong Jung,
and Kijung Shin
IEEE International Conference of Data Mining (ICDM) 2024
MuLe: Multi-Grained Graph Learning for Multi-Behavior Recommendation
Seunghan Lee*,
Geonwoo Ko*,
Hyun-Je Song,
and Jinhong Jung
ACM International Conference on Information and Knowledge Management (CIKM) 2024
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
ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD) 2024
Learning Disentangled Representations in Signed Directed Graphs without Social Assumptions
Geonwoo Ko,
and Jinhong Jung
Random Walk with Restart on Hypergraphs: Fast Computation and an Application to Anomaly Detection
Jaewan Chun,
Geon Lee,
Kijung Shin,
and Jinhong Jung
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
ACM The Web Conference 2023
Time-aware Random Walk Diffusion to Improve Dynamic Graph Learning
Jong-Whi Lee,
and Jinhong Jung
AAAI Conference on Artificial Intelligence (AAAI) 2023
Accurate Node Feature Estimation with Structured Variational Graph Autoencoder
Jaemin Yoo,
Hyunsik Jeon,
Jinhong Jung,
and U Kang
ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD) 2022
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
Random Walk Based Ranking in Signed Social Networks: Model and Algorithms
Jinhong Jung,
Woojeong Jin,
and U Kang
Zoom-SVD: Fast and Memory Efficient Method for Extracting Key Pattern 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
A New Question Answering Approach with Conceptual Graphs
Kyung-Min Kim,
Jinhong Jung,
Jihee Ryu,
Ha-Myung Park,
Joseph P.Joohee,
Seokwoo Jeong,
U Kang,
and Sung-Hyon Myaeng
BePI: Fast and Memory-Efficient Method for Billion-Scale Random Walk with Restart
Jinhong Jung,
Namyong Park,
Lee Sael,
and U Kang
Personalized Ranking in Signed Networks using Signed Random Walk with Restart
Woojeong Jin,
Jinhong Jung,
Lee Sael,
and U Kang
Random Walk with Restart on Large Graphs Using Block Elimination
Jinhong Jung,
Kijung Shin,
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
Domestic Publications
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