Fan Min
Impact in
- Computational Theory and Mathematics top 0.2%
- Rough Sets and Fuzzy Logic
- Information Systems top 0.5%
- Data Mining Algorithms and Applications
- Recommender Systems and Techniques
Papers in
-
- Text and Document Classification Technologies 25
- Imbalanced Data Classification Techniques 19
- Machine Learning and Algorithms 18
- Machine Learning and Data Classification 18
-
- Data Mining Algorithms and Applications 47
- Recommender Systems and Techniques 22
- Co-authors
- William Zhu (30 shared papers)Heng‐Ru Zhang (28 shared papers)Zhiheng Zhang (10 shared papers)Yuhua Qian (1 shared paper)Qihe Liu (5 shared papers)Yu Fang (5 shared papers)Qinghua Hu (2 shared papers)Min Wang (5 shared papers)
- Journals
- Information Sciences (18 papers)Applied Intelligence (12 papers)International Journal of Machine Learning and Cybernetics (11 papers)Knowledge-Based Systems (9 papers)IEEE Access (7 papers)
- Partner nations
- ChinaUnited StatesItaly
In The Last Decade
Fan Min
173 papers receiving 2.6k citations
Peers
Comparison fields: 5 of 120
- Computational Theory and Mathematics 1.4k
- Information Systems 1.1k
- Artificial Intelligence 1.5k
- Signal Processing 340
- Management Science and Operations Research 345
Countries citing papers authored by Fan Min
This map shows the geographic impact of Fan Min'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 Fan Min with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fan Min more than expected).
Fields of papers citing papers by Fan Min
This network shows the impact of papers produced by Fan Min. 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 Fan Min. The network helps show where Fan Min may publish in the future.
Co-authors
The 25 scholars most cited alongside Fan Min, 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 204 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 194 | |
| 2 | 2015 | 174 | |
| 3 | 2013 | 122 | |
| 4 | 2016 | 112 | |
| 5 | 2017 | 93 | |
| 6 | 2012 | 92 | |
| 7 | 2018 | 82 | |
| 8 | 2021 | 76 | |
| 9 | 2009 | 72 | |
| 10 | 2018 | 66 | |
| 11 | 2019 | 62 | |
| 12 | 2021 | 52 | |
| 13 | 2016 | 51 | |
| 14 | 2019 | 51 | |
| 15 | 2017 | 50 | |
| 16 | 2017 | 40 | |
| 17 | 2012 | 39 | |
| 18 | 2012 | 37 | |
| 19 | 2012 | 36 | |
| 20 | 2020 | 35 |
About Fan Min
Fan Min is a scholar working on Artificial Intelligence, Information Systems, Computational Theory and Mathematics, Computer Vision and Pattern Recognition and Signal Processing, having authored 204 papers that have together received 2.7k indexed citations. Recurring topics across this work include Rough Sets and Fuzzy Logic (70 papers), Data Mining Algorithms and Applications (47 papers), Text and Document Classification Technologies (25 papers), Image Retrieval and Classification Techniques (23 papers), Recommender Systems and Techniques (22 papers), Imbalanced Data Classification Techniques (19 papers), Machine Learning and Algorithms (18 papers) and Machine Learning and Data Classification (18 papers). The work is most often cited by research in Computational Theory and Mathematics (1.4k citations), Information Systems (1.1k citations), Artificial Intelligence (1.5k citations), Signal Processing (340 citations) and Management Science and Operations Research (345 citations). Fan Min has collaborated with scholars based in China, United States and Italy. Frequent co-authors include William Zhu, Heng‐Ru Zhang, Zhiheng Zhang, Yuhua Qian, Qihe Liu, Yu Fang, Qinghua Hu, Min Wang, Qingxin Zhu and Shiping Wang. Their work appears in journals such as Information Sciences, Applied Intelligence, International Journal of Machine Learning and Cybernetics, Knowledge-Based Systems and IEEE Access.
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.