Heungmo Ryang
Impact in
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- Rough Sets and Fuzzy Logic
- Information Systems top 1%
- Data Mining Algorithms and Applications
Papers in
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- Data Mining Algorithms and Applications 17
- Web Data Mining and Analysis 2
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- Rough Sets and Fuzzy Logic 15
- Co-authors
- Unil Yun (21 shared papers)Gangin Lee (9 shared papers)Keun Ho Ryu (4 shared papers)Hamido Fujita (1 shared paper)Kyungmin Lee (1 shared paper)Dong-Gyu Kim (1 shared paper)Jiwon Kim (2 shared papers)Eunchul Yoon (1 shared paper)
- Journals
- Knowledge-Based Systems (3 papers)Journal of Intelligent & Fuzzy Systems (2 papers)Expert Systems with Applications (2 papers)Applied Intelligence (1 paper)Engineering Applications of Artificial Intelligence (1 paper)
- Partner nations
- South KoreaUnited StatesJapan
In The Last Decade
Heungmo Ryang
18 papers receiving 776 citations
Peers
Comparison fields: 5 of 49
- Computational Theory and Mathematics 542
- Information Systems 731
- Signal Processing 243
- Artificial Intelligence 474
- Marketing 34
Countries citing papers authored by Heungmo Ryang
This map shows the geographic impact of Heungmo Ryang'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 Heungmo Ryang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Heungmo Ryang more than expected).
Fields of papers citing papers by Heungmo Ryang
This network shows the impact of papers produced by Heungmo Ryang. 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 Heungmo Ryang. The network helps show where Heungmo Ryang may publish in the future.
Co-authors
The 9 scholars most cited alongside Heungmo Ryang, 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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 117 | |
| 2 | 2014 | 97 | |
| 3 | 2016 | 87 | |
| 4 | 2017 | 77 | |
| 5 | 2014 | 69 | |
| 6 | 2016 | 54 | |
| 7 | 2014 | 42 | |
| 8 | 2015 | 41 | |
| 9 | 2015 | 38 | |
| 10 | 2016 | 34 | |
| 11 | 2016 | 31 | |
| 12 | 2016 | 30 | |
| 13 | 2016 | 22 | |
| 14 | 2016 | 18 | |
| 15 | 2013 | 12 | |
| 16 | 2015 | 10 | |
| 17 | 2014 | 4 | |
| 18 | 2013 | 2 | |
| 19 | 2016 | 1 | |
| 20 | 2015 | 1 |
About Heungmo Ryang
Heungmo Ryang is a scholar working on Information Systems, Computational Theory and Mathematics, Artificial Intelligence, Signal Processing and Computer Networks and Communications, having authored 21 papers that have together received 787 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (17 papers), Rough Sets and Fuzzy Logic (15 papers), Imbalanced Data Classification Techniques (7 papers), Data Management and Algorithms (6 papers), Web Data Mining and Analysis (2 papers), Algorithms and Data Compression (2 papers), Data Stream Mining Techniques (2 papers) and Advanced Database Systems and Queries (1 paper). The work is most often cited by research in Computational Theory and Mathematics (542 citations), Information Systems (731 citations), Signal Processing (243 citations), Artificial Intelligence (474 citations) and Marketing (34 citations). Heungmo Ryang has collaborated with scholars based in South Korea, United States and Japan. Frequent co-authors include Unil Yun, Gangin Lee, Keun Ho Ryu, Hamido Fujita, Kyungmin Lee, Dong-Gyu Kim, Jiwon Kim, Eunchul Yoon and Chulhong Kim. Their work appears in journals such as Knowledge-Based Systems, Journal of Intelligent & Fuzzy Systems, Expert Systems with Applications, Applied Intelligence and Engineering Applications of Artificial Intelligence.
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.