Sunhao Dai
Impact in
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- Recommender Systems and Techniques
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- Topic Modeling
- Advanced Graph Neural Networks
- Machine Learning and Algorithms
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
Papers in
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- Natural Language Processing Techniques 3
- Topic Modeling 3
- Advanced Text Analysis Techniques 2
- Data Stream Mining Techniques 2
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- Recommender Systems and Techniques 8
- Expert finding and Q&A systems 1
- Co-authors
- Jun Xu (14 shared papers)Xiao Zhang (5 shared papers)Ji-Rong Wen (6 shared papers)Zhenhua Dong (6 shared papers)Quanyu Dai (2 shared papers)Liang Pang (5 shared papers)Hengyi Cai (1 shared paper)Shuaiqiang Wang (1 shared paper)
- Journals
- Frontiers of Computer Science (1 paper)arXiv (Cornell University) (3 papers)Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Sunhao Dai
13 papers receiving 67 citations
Peers
Comparison fields: 5 of 31
- Information Systems 35
- Artificial Intelligence 39
- Management Science and Operations Research 15
- Health Informatics 1
- Signal Processing 5
Countries citing papers authored by Sunhao Dai
This map shows the geographic impact of Sunhao Dai'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 Sunhao Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sunhao Dai more than expected).
Fields of papers citing papers by Sunhao Dai
This network shows the impact of papers produced by Sunhao Dai. 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 Sunhao Dai. The network helps show where Sunhao Dai may publish in the future.
Co-authors
The 25 scholars most cited alongside Sunhao Dai, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 15 | |
| 2 | 2025 | 13 | |
| 3 | 2024 | 10 | |
| 4 | 2023 | 5 | |
| 5 | 2024 | 4 | |
| 6 | 2024 | 4 | |
| 7 | 2024 | 4 | |
| 8 | 2024 | 4 | |
| 9 | 2025 | 3 | |
| 10 | 2024 | 2 | |
| 11 | 2025 | 1 | |
| 12 | 2025 | 1 | |
| 13 | 2024 | 1 | |
| 14 | 2025 | 0 | |
| 15 | 2024 | 0 |
About Sunhao Dai
Sunhao Dai is a scholar working on Artificial Intelligence, Information Systems, Management Science and Operations Research, Computer Vision and Pattern Recognition and Molecular Biology, having authored 15 papers that have together received 67 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (8 papers), Advanced Bandit Algorithms Research (5 papers), Natural Language Processing Techniques (3 papers), Topic Modeling (3 papers), Advanced Text Analysis Techniques (2 papers), Data Stream Mining Techniques (2 papers), Image and Video Quality Assessment (1 paper) and Expert finding and Q&A systems (1 paper). The work is most often cited by research in Information Systems (35 citations), Artificial Intelligence (39 citations), Management Science and Operations Research (15 citations), Health Informatics (1 citation) and Signal Processing (5 citations). Sunhao Dai has collaborated with scholars based in China and United States. Frequent co-authors include Jun Xu, Xiao Zhang, Ji-Rong Wen, Zhenhua Dong, Quanyu Dai, Liang Pang, Hengyi Cai, Shuaiqiang Wang, Dawei Yin and Xiaochi Wei. Their work appears in journals such as Frontiers of Computer Science, arXiv (Cornell University) and Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
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.