Kan Li
Impact in
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- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
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- Online Learning and Analytics
Papers in
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- Topic Modeling 20
- Speech and dialogue systems 14
- Natural Language Processing Techniques 8
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- Human Pose and Action Recognition 10
- Multimodal Machine Learning Applications 9
- Co-authors
- Sadique Ahmad (7 shared papers)Guangquan Zhang (6 shared papers)Jie Lü (6 shared papers)Yushu Liu (9 shared papers)Heyan Huang (1 shared paper)Lin Zhang (1 shared paper)Shuhui Zhang (2 shared papers)Yongchao Wang (2 shared papers)
In The Last Decade
Kan Li
90 papers receiving 981 citations
Peers
Comparison fields: 5 of 105
- Statistical and Nonlinear Physics 250
- Computer Science Applications 97
- Artificial Intelligence 434
- Information Systems 270
- Computer Vision and Pattern Recognition 200
Countries citing papers authored by Kan Li
This map shows the geographic impact of Kan 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 Kan Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kan Li more than expected).
Fields of papers citing papers by Kan Li
This network shows the impact of papers produced by Kan 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 Kan Li. The network helps show where Kan Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Kan 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 99 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 109 | |
| 2 | 2019 | 94 | |
| 3 | 2018 | 54 | |
| 4 | 2018 | 51 | |
| 5 | 2018 | 37 | |
| 6 | 2019 | 35 | |
| 7 | 2019 | 32 | |
| 8 | 2020 | 30 | |
| 9 | 2019 | 25 | |
| 10 | 2017 | 25 | |
| 11 | 2009 | 24 | |
| 12 | 2016 | 24 | |
| 13 | 2018 | 24 | |
| 14 | 2019 | 23 | |
| 15 | 2020 | 22 | |
| 16 | 2015 | 22 | |
| 17 | 2020 | 21 | |
| 18 | 2021 | 19 | |
| 19 | 2019 | 18 | |
| 20 | 2019 | 17 |
About Kan Li
Kan Li is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Statistical and Nonlinear Physics and Computer Networks and Communications, having authored 99 papers that have together received 1.0k indexed citations. Recurring topics across this work include Topic Modeling (20 papers), Complex Network Analysis Techniques (16 papers), Speech and dialogue systems (14 papers), Opinion Dynamics and Social Influence (14 papers), Human Pose and Action Recognition (10 papers), Multimodal Machine Learning Applications (9 papers), Recommender Systems and Techniques (9 papers) and Natural Language Processing Techniques (8 papers). The work is most often cited by research in Statistical and Nonlinear Physics (250 citations), Computer Science Applications (97 citations), Artificial Intelligence (434 citations), Information Systems (270 citations) and Computer Vision and Pattern Recognition (200 citations). Kan Li has collaborated with scholars based in China, Australia and Pakistan. Frequent co-authors include Sadique Ahmad, Guangquan Zhang, Jie Lü, Yushu Liu, Heyan Huang, Lin Zhang, Shuhui Zhang, Yongchao Wang, Arshad Ahmad and Fengjiao Chen. Their work appears in journals such as Knowledge-Based Systems, Neurocomputing, IEEE Access, Applied Intelligence and Applied 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.