Jae‐Hoon Kim
- Global and Planetary Change top 5%
- Atmospheric Science top 10%
- Oceanography top 5%
- Artificial Intelligence top 10%
- Control and Systems Engineering top 10%
- Co-authors
- Kei May LauDuane E. WaliserMoussa HamadacheDongik LeeSatyendra KumarJeong-Wook LeeJungyun SeoKyo-Il Lee
- Topics
- Natural Language Processing Techniques (22 papers)Topic Modeling (16 papers)Advanced Text Analysis Techniques (6 papers)
- Partner nations
- South KoreaUnited StatesUnited Kingdom
In The Last Decade
Jae‐Hoon Kim
48 papers receiving 530 citations
Peers
Comparison fields: 5 of 90
- Global and Planetary Change 301
- Atmospheric Science 260
- Oceanography 190
- Artificial Intelligence 96
- Control and Systems Engineering 71
Countries citing papers authored by Jae‐Hoon Kim
This map shows the geographic impact of Jae‐Hoon Kim'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 Jae‐Hoon Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jae‐Hoon Kim more than expected).
Fields of papers citing papers by Jae‐Hoon Kim
This network shows the impact of papers produced by Jae‐Hoon Kim. 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 Jae‐Hoon Kim. The network helps show where Jae‐Hoon Kim may publish in the future.
Co-authorship network of co-authors of Jae‐Hoon Kim
This figure shows the co-authorship network connecting the top 25 collaborators of Jae‐Hoon Kim. A scholar is included among the top collaborators of Jae‐Hoon Kim based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jae‐Hoon Kim. Jae‐Hoon Kim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 7 | |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 4 | |
| 8 | 0 | |
| 9 | 0 | |
| 10 | 1 | |
| 11 | 4 | |
| 12 | Detecting Errors in POS-Tagged Corpus on XGBoost and Cross Validation | 0 |
| 13 | 6 | |
| 14 | An Efficiency Revaluation of Graph Labeling for subClassOf Inference based on OWLJessKB Inference Rules | 0 |
| 15 | The effective kinematic calibration method of industrial manipulators using IGPS | 2 |
| 16 | 2 | |
| 17 | Semi-Automatic Annotation Tool to Build Large Dependency Tree-Tagged Corpus | 0 |
| 18 | Satellite Ground Track Display on a Digitized World Map for the KOMPSAT-2 Mission Operations | 3 |
| 19 | Application Ways of Virtual Reality Technology in Sport Image Training | 0 |
| 20 | A Hidden Markov Model Imbedding Multiword Units for Part-of-Speech Tagging | 2 |
About Jae‐Hoon Kim
Jae‐Hoon Kim is a scholar working on Artificial Intelligence, Information Systems and Developmental Biology, having authored 72 papers that have together received 587 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (22 papers), Topic Modeling (16 papers) and Advanced Text Analysis Techniques (6 papers). The work is most often cited by research in Oceanography (190 citations), Atmospheric Science (260 citations) and Global and Planetary Change (301 citations). Jae‐Hoon Kim has collaborated with scholars based in South Korea, United States and United Kingdom. Frequent co-authors include Kei May Lau, Duane E. Waliser, Moussa Hamadache, Dongik Lee, Satyendra Kumar, Jeong-Wook Lee, Jungyun Seo, Kyo-Il Lee, Keum‐Shik Hong and Anders Larsson. Their work appears in journals such as Applied Physics Letters, Scientific Reports and Journal of the Atmospheric Sciences.
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.