Deyu Li
Impact in
- Computational Theory and Mathematics top 0.2%
- Rough Sets and Fuzzy Logic
- Advanced Algebra and Logic
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- Multi-Criteria Decision Making
Papers in
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- Text and Document Classification Technologies 26
- Sentiment Analysis and Opinion Mining 23
- Topic Modeling 20
- Advanced Computational Techniques and Applications 16
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- Rough Sets and Fuzzy Logic 74
- Advanced Algebra and Logic 12
- Co-authors
- Chao Zhang (36 shared papers)Jiye Liang (12 shared papers)Suge Wang (41 shared papers)Yanhui Zhai (26 shared papers)Xiuyun Guo (3 shared papers)Mark J. Wierman (1 shared paper)Zhicai Shi (1 shared paper)Chuangyin Dang (4 shared papers)
In The Last Decade
Deyu Li
168 papers receiving 3.0k citations
Peers
Comparison fields: 5 of 137
- Computational Theory and Mathematics 1.5k
- Management Science and Operations Research 955
- Artificial Intelligence 1.6k
- Discrete Mathematics and Combinatorics 132
- Information Systems 757
Countries citing papers authored by Deyu Li
This map shows the geographic impact of Deyu Li'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 Deyu Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deyu Li more than expected).
Fields of papers citing papers by Deyu Li
This network shows the impact of papers produced by Deyu Li. 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 Deyu Li. The network helps show where Deyu Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Deyu Li, 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 181 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2006 | 240 | |
| 2 | 2011 | 156 | |
| 3 | 2019 | 152 | |
| 4 | 2011 | 106 | |
| 5 | 2011 | 94 | |
| 6 | 2010 | 86 | |
| 7 | 2007 | 74 | |
| 8 | 2016 | 70 | |
| 9 | 2016 | 63 | |
| 10 | 1998 | 63 | |
| 11 | 2000 | 62 | |
| 12 | 2016 | 59 | |
| 13 | 2019 | 57 | |
| 14 | 2012 | 51 | |
| 15 | 2022 | 51 | |
| 16 | 2012 | 48 | |
| 17 | 2019 | 46 | |
| 18 | 2004 | 46 | |
| 19 | 2021 | 45 | |
| 20 | 2000 | 44 |
About Deyu Li
Deyu Li is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Management Science and Operations Research, Information Systems and Computer Vision and Pattern Recognition, having authored 181 papers that have together received 3.1k indexed citations. Recurring topics across this work include Rough Sets and Fuzzy Logic (74 papers), Multi-Criteria Decision Making (44 papers), Text and Document Classification Technologies (26 papers), Sentiment Analysis and Opinion Mining (23 papers), Data Mining Algorithms and Applications (21 papers), Topic Modeling (20 papers), Advanced Computational Techniques and Applications (16 papers) and Advanced Algebra and Logic (12 papers). The work is most often cited by research in Computational Theory and Mathematics (1.5k citations), Management Science and Operations Research (955 citations), Artificial Intelligence (1.6k citations), Discrete Mathematics and Combinatorics (132 citations) and Information Systems (757 citations). Deyu Li has collaborated with scholars based in China, Singapore and Taiwan. Frequent co-authors include Chao Zhang, Jiye Liang, Suge Wang, Yanhui Zhai, Xiuyun Guo, Mark J. Wierman, Zhicai Shi, Chuangyin Dang, Fuyuan Cao and Jianming Zhan. Their work appears in journals such as Information Sciences, Knowledge-Based Systems, International Journal of Machine Learning and Cybernetics, International Journal of Approximate Reasoning and Symmetry.
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.