Augmenting Mobile Search Engine with Semantic Web and Context Awareness. - Sangjin Shin; Dong-Hoon Shin; Jihoon Ko; Minjae Song; Sungkwang Eom; Kyong-Ho Lee; Jinsung Park; Seungwon Lee; Jooyeon Jung (Web Intelligence/IAT Workshops, 2013)

Semantic search for smart mobile devices. - Sangjin Shin; Jihoon Ko; Dong-Hoon Shin; Jooik Jung; Kyong-Ho Lee (IUI Companion, 2013)

Keyword Based Semantic Search for Mobile Data. - Jihoon Ko; Sangjin Shin; Sungkwang Eom; Minjae Song; Jooik Jung; Dong-Hoon Shin; Kyong-Ho Lee; Yongil Jang (MDM (1), 2014)

Semantically enhanced keyword search for smartphones. - Jihoon Ko; Sangjin Shin; Sungkwang Eom; Minjae Song; Dong-Hoon Shin; Kyong-Ho Lee; Yongil Jang (WWW (Companion Volume), 2014)

Keyword-based mobile semantic search using mobile ontology. - Sangjin Shin; Jihoon Ko; Sungkwang Eom; Minjae Song; Dong-Hoon Shin; Kyong-Ho Lee (J. Inf. Sci., 2015)

Prototyping Functional Android App Features with ProDroid. - Donghwi Kim; Soo Young Park; Jihoon Ko; Steven Y. Ko; Sung-Ju Lee (MobiSys, 2019)

X-Droid: A Quick and Easy Android Prototyping Framework with a Single-App Illusion. - Donghwi Kim; Sooyoung Park; Jihoon Ko; Steven Y. Ko; Sung-Ju Lee (UIST, 2019)

MONSTOR: An Inductive Approach for Estimating and Maximizing Influence over Unseen Networks. - Jihoon Ko; Kyuhan Lee; Kijung Shin; Noseong Park (ASONAM, 2020)

Evolution of Real-world Hypergraphs: Patterns and Models without Oracles. - Yunbum Kook; Jihoon Ko; Kijung Shin (ICDM, 2020)

Incremental Lossless Graph Summarization. - Jihoon Ko; Yunbum Kook; Kijung Shin (KDD, 2020)

SSumM: Sparse Summarization of Massive Graphs. - Kyuhan Lee; Hyeonsoo Jo; Jihoon Ko; Sungsu Lim; Kijung Shin (KDD, 2020)

MONSTOR: An Inductive Approach for Estimating and Maximizing Influence over Unseen Social Networks. - Jihoon Ko; Kyuhan Lee; Kijung Shin; Noseong Park (CoRR, 2020)

Hypergraph Motifs: Concepts, Algorithms, and Discoveries. - Geon Lee; Jihoon Ko; Kijung Shin (Proc. VLDB Endow., 2020)

Learning to Pool in Graph Neural Networks for Extrapolation. - Jihoon Ko; Taehyung Kwon; Kijung Shin; Juho Lee 001 (CoRR, 2021)

SLUGGER: Lossless Hierarchical Summarization of Massive Graphs. - Kyuhan Lee; Jihoon Ko; Kijung Shin (ICDE, 2022)

Deep-Learning-Based Precipitation Nowcasting with Ground Weather Station Data and Radar Data. - Jihoon Ko; Kyuhan Lee; Hyunjin Hwang; Kijung Shin (ICDM (Workshops), 2022)

BeGin: Extensive Benchmark Scenarios and An Easy-to-use Framework for Graph Continual Learning. - Jihoon Ko; Shinhwan Kang; Kijung Shin (CoRR, 2022)

Effective training strategies for deep-learning-based precipitation nowcasting and estimation. - Jihoon Ko; Kyuhan Lee; Hyunjin Hwang; Seok-Geun Oh; Seok-Woo Son; Kijung Shin (Comput. Geosci., 2022)

Growth patterns and models of real-world hypergraphs. - Jihoon Ko; Yunbum Kook; Kijung Shin (Knowl. Inf. Syst., 2022)

TensorCodec: Compact Lossy Compression of Tensors without Strong Data Assumptions. - Taehyung Kwon; Jihoon Ko; Jinhong Jung; Kijung Shin (ICDM, 2023)

Characterization of Simplicial Complexes by Counting Simplets Beyond Four Nodes. - Hyunju Kim; Jihoon Ko; Fanchen Bu; Kijung Shin (WWW, 2023)

NeuKron: Constant-Size Lossy Compression of Sparse Reorderable Matrices and Tensors. - Taehyung Kwon; Jihoon Ko; Jinhong Jung; Kijung Shin (WWW, 2023)

ELiCiT: Effective and Lightweight Lossy Compression of Tensors. - Jihoon Ko; Taehyung Kwon; Jinhong Jung; Kijung Shin (ICDM, 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; Kijung Shin (KDD, 2024)

Hypergraph motifs and their extensions beyond binary. - Geon Lee; Seokbum Yoon; Jihoon Ko; Hyunju Kim; Kijung Shin (VLDB J., 2024)

DiffIM: Differentiable Influence Minimization with Surrogate Modeling and Continuous Relaxation. - Junghun Lee; Hyunju Kim; Fanchen Bu; Jihoon Ko; Kijung Shin (AAAI, 2025)

Kronecker Generative Models for Power-Law Patterns in Real-World Hypergraphs. - Minyoung Choe; Jihoon Ko; Taehyung Kwon; Kijung Shin; Christos Faloutsos (WWW, 2025)

Compact lossy compression of tensors via neural tensor-train decomposition. - Taehyung Kwon; Jihoon Ko; Jinhong Jung; Jun-Gi Jang; Kijung Shin (Knowl. Inf. Syst., 2025)

BeGin: Extensive Benchmark Scenarios and an Easy-to-use Framework for Graph Continual Learning. - Jihoon Ko; Shinhwan Kang; Taehyung Kwon; Heechan Moon; Kijung Shin (ACM Trans. Intell. Syst. Technol., 2025)

Estimating simplet counts via sampling. - Hyunju Kim; Heechan Moon; Fanchen Bu; Jihoon Ko; Kijung Shin (VLDB J., 2025)