Chenyun Yu
Impact in
- Information Systems top 10%
- Recommender Systems and Techniques
- Artificial Intelligence top 10%
- Topic Modeling
- Advanced Graph Neural Networks
- Authorship Attribution and Profiling
- Cryptography and Data Security
Papers in
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- Topic Modeling 5
- Advanced Graph Neural Networks 4
- Authorship Attribution and Profiling 3
- Algorithms and Data Compression 2
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- Recommender Systems and Techniques 5
- Expert finding and Q&A systems 2
- Co-authors
- Sarana Nutanong (10 shared papers)K.C. Lam (3 shared papers)Ping Yung (2 shared papers)Cong Wang (3 shared papers)Xingliang Yuan (3 shared papers)Thanawin Rakthanmanon (3 shared papers)Raheem Sarwar (3 shared papers)Guoqiang Shu (1 shared paper)
In The Last Decade
Chenyun Yu
24 papers receiving 267 citations
Peers
Comparison fields: 5 of 61
- Information Systems 106
- Artificial Intelligence 135
- Building and Construction 43
- Signal Processing 31
- Computer Vision and Pattern Recognition 50
Countries citing papers authored by Chenyun Yu
This map shows the geographic impact of Chenyun Yu'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 Chenyun Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chenyun Yu more than expected).
Fields of papers citing papers by Chenyun Yu
This network shows the impact of papers produced by Chenyun Yu. 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 Chenyun Yu. The network helps show where Chenyun Yu may publish in the future.
Co-authors
The 25 scholars most cited alongside Chenyun Yu, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 46 | |
| 2 | 2012 | 41 | |
| 3 | 2017 | 27 | |
| 4 | 2018 | 23 | |
| 5 | 2020 | 15 | |
| 6 | 2024 | 15 | |
| 7 | 2016 | 15 | |
| 8 | 2018 | 14 | |
| 9 | 2012 | 12 | |
| 10 | 2016 | 11 | |
| 11 | 2014 | 10 | |
| 12 | 2018 | 9 | |
| 13 | 2018 | 8 | |
| 14 | 2022 | 5 | |
| 15 | 2013 | 5 | |
| 16 | 2012 | 4 | |
| 17 | 2024 | 4 | |
| 18 | 2025 | 3 | |
| 19 | 2011 | 2 | |
| 20 | 2025 | 1 |
About Chenyun Yu
Chenyun Yu is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Computer Networks and Communications and Building and Construction, having authored 26 papers that have together received 274 indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Recommender Systems and Techniques (5 papers), Advanced Image and Video Retrieval Techniques (5 papers), Advanced Graph Neural Networks (4 papers), Chaos-based Image/Signal Encryption (3 papers), Authorship Attribution and Profiling (3 papers), Expert finding and Q&A systems (2 papers) and Algorithms and Data Compression (2 papers). The work is most often cited by research in Information Systems (106 citations), Artificial Intelligence (135 citations), Building and Construction (43 citations), Signal Processing (31 citations) and Computer Vision and Pattern Recognition (50 citations). Chenyun Yu has collaborated with scholars based in Hong Kong, China and Thailand. Frequent co-authors include Sarana Nutanong, K.C. Lam, Ping Yung, Cong Wang, Xingliang Yuan, Thanawin Rakthanmanon, Raheem Sarwar, Guoqiang Shu, Di Niu and Hangyu Li. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Knowledge-Based Systems, IEEE Access, Neurocomputing and Habitat International.
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.