Ning Yang
Impact in
- Information Systems top 5%
- Recommender Systems and Techniques
- Artificial Intelligence top 10%
- Advanced Graph Neural Networks
- Topic Modeling
- AI in cancer detection
Papers in
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- Advanced Graph Neural Networks 10
- Sentiment Analysis and Opinion Mining 3
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- Recommender Systems and Techniques 11
- Co-authors
- Philip S. Yu (14 shared papers)Yi Wu (1 shared paper)Jing Ning (1 shared paper)Yuan‐Wei Du (1 shared paper)Yao Zhao (1 shared paper)Ruochen Li (1 shared paper)Paul Quinton (1 shared paper)Xueqi Zhang (1 shared paper)
- Journals
- Knowledge-Based Systems (3 papers)Information Sciences (2 papers)Discrete Applied Mathematics (2 papers)World Wide Web (2 papers)IEEE Transactions on Knowledge and Data Engineering (2 papers)
- Partner nations
- ChinaUnited StatesFrance
In The Last Decade
Ning Yang
53 papers receiving 463 citations
Peers
Comparison fields: 5 of 115
- Information Systems 132
- Artificial Intelligence 183
- Computational Mathematics 3
- Management Science and Operations Research 54
- Statistical and Nonlinear Physics 48
Countries citing papers authored by Ning Yang
This map shows the geographic impact of Ning Yang'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 Ning Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ning Yang more than expected).
Fields of papers citing papers by Ning Yang
This network shows the impact of papers produced by Ning Yang. 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 Ning Yang. The network helps show where Ning Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside Ning Yang, 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 62 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 51 | |
| 2 | 2022 | 48 | |
| 3 | 2023 | 37 | |
| 4 | 2018 | 28 | |
| 5 | 2019 | 25 | |
| 6 | 2022 | 23 | |
| 7 | 2023 | 21 | |
| 8 | 2020 | 20 | |
| 9 | 2023 | 18 | |
| 10 | 2023 | 17 | |
| 11 | 2014 | 16 | |
| 12 | 2024 | 14 | |
| 13 | 2009 | 14 | |
| 14 | 2019 | 13 | |
| 15 | 2022 | 12 | |
| 16 | 2017 | 10 | |
| 17 | 2021 | 9 | |
| 18 | 2007 | 8 | |
| 19 | 2022 | 7 | |
| 20 | 2022 | 6 |
About Ning Yang
Ning Yang is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Computational Theory and Mathematics and Geometry and Topology, having authored 62 papers that have together received 478 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (11 papers), Advanced Graph Neural Networks (10 papers), Graph theory and applications (6 papers), Advanced Graph Theory Research (4 papers), Cardiac Imaging and Diagnostics (4 papers), Complex Network Analysis Techniques (4 papers), Sentiment Analysis and Opinion Mining (3 papers) and Advanced Neural Network Applications (3 papers). The work is most often cited by research in Information Systems (132 citations), Artificial Intelligence (183 citations), Computational Mathematics (3 citations), Management Science and Operations Research (54 citations) and Statistical and Nonlinear Physics (48 citations). Ning Yang has collaborated with scholars based in China, United States and France. Frequent co-authors include Philip S. Yu, Yi Wu, Jing Ning, Yuan‐Wei Du, Yao Zhao, Ruochen Li, Paul Quinton, Xueqi Zhang, Zewen Chen and Sam Kwong. Their work appears in journals such as Knowledge-Based Systems, Information Sciences, Discrete Applied Mathematics, World Wide Web and IEEE Transactions on Knowledge and Data Engineering.
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.