Hyunsouk Cho
Impact in
- Information Systems top 5%
- Recommender Systems and Techniques
- Artificial Intelligence top 5%
- Topic Modeling
- Advanced Graph Neural Networks
- Domain Adaptation and Few-Shot Learning
Papers in
-
- Topic Modeling 7
- Advanced Text Analysis Techniques 4
- Natural Language Processing Techniques 3
-
- Recommender Systems and Techniques 5
- Co-authors
- Sehee Chung (6 shared papers)Hoyeop Lee (4 shared papers)Jinbae Im (2 shared papers)Seongwon Jang (3 shared papers)Jongwuk Lee (4 shared papers)Seung-won Hwang (5 shared papers)Jinyoung Yeo (4 shared papers)H. J. Kim (1 shared paper)
- Journals
- IEEE Access (2 papers)IEEE Transactions on Knowledge and Data Engineering (2 papers)Language Resources and Evaluation (1 paper)International Journal of Pharmaceutics (1 paper)The VLDB Journal (1 paper)
- Partner nations
- South KoreaSwedenAustria
In The Last Decade
Hyunsouk Cho
18 papers receiving 315 citations
Peers
Comparison fields: 5 of 44
- Information Systems 207
- Artificial Intelligence 223
- Management Science and Operations Research 75
- Computer Vision and Pattern Recognition 68
- Signal Processing 32
Countries citing papers authored by Hyunsouk Cho
This map shows the geographic impact of Hyunsouk Cho's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hyunsouk Cho with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hyunsouk Cho more than expected).
Fields of papers citing papers by Hyunsouk Cho
This network shows the impact of papers produced by Hyunsouk Cho. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hyunsouk Cho. The network helps show where Hyunsouk Cho may publish in the future.
Co-authors
The 22 scholars most cited alongside Hyunsouk Cho, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 217 | |
| 2 | 2021 | 21 | |
| 3 | 2024 | 10 | |
| 4 | 2013 | 9 | |
| 5 | 2012 | 9 | |
| 6 | 2020 | 9 | |
| 7 | 2024 | 7 | |
| 8 | 2024 | 7 | |
| 9 | 2018 | 6 | |
| 10 | 2013 | 6 | |
| 11 | SQuAD2-CR: Semi-supervised Annotation for Cause and Rationales for Unanswerability in SQuAD 2.0 | 2020 | 5 |
| 12 | 2022 | 5 | |
| 13 | 2017 | 4 | |
| 14 | 2022 | 4 | |
| 15 | 2016 | 3 | |
| 16 | 2025 | 2 | |
| 17 | 2024 | 1 | |
| 18 | 2017 | 1 | |
| 19 | 2025 | 0 | |
| 20 | 2018 | 0 |
About Hyunsouk Cho
Hyunsouk Cho is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Signal Processing and Management Science and Operations Research, having authored 22 papers that have together received 326 indexed citations. Recurring topics across this work include Topic Modeling (7 papers), Data Management and Algorithms (5 papers), Recommender Systems and Techniques (5 papers), Advanced Text Analysis Techniques (4 papers), Natural Language Processing Techniques (3 papers), Advanced Image and Video Retrieval Techniques (3 papers), Advanced Bandit Algorithms Research (3 papers) and Stock Market Forecasting Methods (2 papers). The work is most often cited by research in Information Systems (207 citations), Artificial Intelligence (223 citations), Management Science and Operations Research (75 citations), Computer Vision and Pattern Recognition (68 citations) and Signal Processing (32 citations). Hyunsouk Cho has collaborated with scholars based in South Korea, Sweden and Austria. Frequent co-authors include Sehee Chung, Hoyeop Lee, Jinbae Im, Seongwon Jang, Jongwuk Lee, Seung-won Hwang, Jinyoung Yeo, H. J. Kim, Seung-won Hwang and Ji-Rong Wen. Their work appears in journals such as IEEE Access, IEEE Transactions on Knowledge and Data Engineering, Language Resources and Evaluation, International Journal of Pharmaceutics and The VLDB Journal.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.