Seok‐Hee Hong
- Computer Vision and Pattern Recognition top 5%
- Statistical and Nonlinear Physics top 5%
- Artificial Intelligence
- Computational Theory and Mathematics top 10%
- Sociology and Political Science
- Co-authors
- Peter EadesWeidong HuangQuan NguyenKai XuDirk KoschützkiFalk SchreiberTim DwyerChun‐Cheng Lin
- Topics
- Data Visualization and Analytics (25 papers)Complex Network Analysis Techniques (14 papers)Topological and Geometric Data Analysis (9 papers)
- Cited by
- Computer Vision and Pattern RecognitionStatistical and Nonlinear PhysicsComputer Graphics and Computer-Aided Design
- Partner nations
- AustraliaJapanUnited States
In The Last Decade
Seok‐Hee Hong
33 papers receiving 259 citations
Peers
Comparison fields: 5 of 60
- Computer Vision and Pattern Recognition 197
- Statistical and Nonlinear Physics 102
- Artificial Intelligence 71
- Computational Theory and Mathematics 46
- Sociology and Political Science 27
Countries citing papers authored by Seok‐Hee Hong
This map shows the geographic impact of Seok‐Hee Hong'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 Seok‐Hee Hong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seok‐Hee Hong more than expected).
Fields of papers citing papers by Seok‐Hee Hong
This network shows the impact of papers produced by Seok‐Hee Hong. 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 Seok‐Hee Hong. The network helps show where Seok‐Hee Hong may publish in the future.
Co-authorship network of co-authors of Seok‐Hee Hong
This figure shows the co-authorship network connecting the top 25 collaborators of Seok‐Hee Hong. A scholar is included among the top collaborators of Seok‐Hee Hong 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 Seok‐Hee Hong. Seok‐Hee Hong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 13 | |
| 2 | 1 | |
| 3 | 10 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | 7 | |
| 8 | 1 | |
| 9 | 4 | |
| 10 | 2 | |
| 11 | 17 | |
| 12 | 8 | |
| 13 | 2 | |
| 14 | 21 | |
| 15 | 3 | |
| 16 | 19 | |
| 17 | 10 | |
| 18 | 31 | |
| 19 | How People Read Sociograms: A Questionnaire Study | 15 |
| 20 | 8 |
About Seok‐Hee Hong
Seok‐Hee Hong is a scholar working on Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics and Computational Theory and Mathematics, having authored 34 papers that have together received 281 indexed citations. Recurring topics across this work include Data Visualization and Analytics (25 papers), Complex Network Analysis Techniques (14 papers) and Topological and Geometric Data Analysis (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (197 citations), Statistical and Nonlinear Physics (102 citations) and Computer Graphics and Computer-Aided Design (17 citations). Seok‐Hee Hong has collaborated with scholars based in Australia, Japan and United States. Frequent co-authors include Peter Eades, Weidong Huang, Quan Nguyen, Quan Nguyen, Kai Xu, Dirk Koschützki, Falk Schreiber, Tim Dwyer, Chun‐Cheng Lin and An Nguyen. Their work appears in journals such as PROTEOMICS, IEEE Transactions on Visualization and Computer Graphics and Computer Graphics Forum.
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.