Chaokun Wang
Impact in
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- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
- Information Systems top 1%
- Recommender Systems and Techniques
Papers in
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- Advanced Graph Neural Networks 38
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- Recommender Systems and Techniques 21
- Co-authors
- Jianmin Wang (43 shared papers)Jun Zhang (7 shared papers)Jeffrey Xu Yu (8 shared papers)Zhipeng Cai (8 shared papers)Xiaojun Ye (10 shared papers)Yingshu Li (2 shared papers)Jiguo Yu (2 shared papers)Meng Wang (2 shared papers)
- Journals
- IEEE Transactions on Knowledge and Data Engineering (9 papers)Proceedings of the VLDB Endowment (3 papers)World Wide Web (3 papers)ACM Transactions on Knowledge Discovery from Data (2 papers)Lecture notes in computer science (18 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Chaokun Wang
129 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 100
- Statistical and Nonlinear Physics 405
- Information Systems 588
- Signal Processing 254
- Artificial Intelligence 756
- Computer Networks and Communications 460
Countries citing papers authored by Chaokun Wang
This map shows the geographic impact of Chaokun Wang'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 Chaokun Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chaokun Wang more than expected).
Fields of papers citing papers by Chaokun Wang
This network shows the impact of papers produced by Chaokun Wang. 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 Chaokun Wang. The network helps show where Chaokun Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Chaokun Wang, 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 143 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 131 | |
| 2 | 2017 | 117 | |
| 3 | 2017 | 83 | |
| 4 | 2010 | 83 | |
| 5 | 2017 | 62 | |
| 6 | 2020 | 55 | |
| 7 | 2010 | 41 | |
| 8 | 2014 | 41 | |
| 9 | 2016 | 38 | |
| 10 | 2015 | 36 | |
| 11 | 2023 | 35 | |
| 12 | 2018 | 34 | |
| 13 | 2019 | 33 | |
| 14 | 2010 | 33 | |
| 15 | 2020 | 31 | |
| 16 | 2016 | 29 | |
| 17 | 2019 | 23 | |
| 18 | 2023 | 22 | |
| 19 | 2018 | 22 | |
| 20 | 2020 | 20 |
About Chaokun Wang
Chaokun Wang is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics and Computer Networks and Communications, having authored 143 papers that have together received 1.7k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (41 papers), Advanced Graph Neural Networks (38 papers), Recommender Systems and Techniques (21 papers), Data Management and Algorithms (18 papers), Music and Audio Processing (15 papers), Graph Theory and Algorithms (13 papers), Music Technology and Sound Studies (11 papers) and Peer-to-Peer Network Technologies (11 papers). The work is most often cited by research in Statistical and Nonlinear Physics (405 citations), Information Systems (588 citations), Signal Processing (254 citations), Artificial Intelligence (756 citations) and Computer Networks and Communications (460 citations). Chaokun Wang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Jianmin Wang, Jun Zhang, Jeffrey Xu Yu, Zhipeng Cai, Xiaojun Ye, Yingshu Li, Jiguo Yu, Meng Wang, Philip S. Yu and Zheng Wang. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Proceedings of the VLDB Endowment, World Wide Web, ACM Transactions on Knowledge Discovery from Data and Lecture notes in computer science.
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.