Qing Da
Impact in
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- Advanced Bandit Algorithms Research
- Information Systems top 5%
- Recommender Systems and Techniques
Papers in
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- Reinforcement Learning in Robotics 6
- Data Stream Mining Techniques 5
- Machine Learning and Data Classification 3
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- Recommender Systems and Techniques 4
- Advanced Decision-Making Techniques 2
- Co-authors
- Anxiang Zeng (7 shared papers)Yang Yu (4 shared papers)Shiyong Chen (2 shared papers)Zhi‐Hua Zhou (4 shared papers)Yu Yang (2 shared papers)Yujing Hu (1 shared paper)Yinghui Xu (1 shared paper)Jing-Cheng Shi (2 shared papers)
- Journals
- IEEE Transactions on Neural Networks and Learning Systems (1 paper)IEEE Transactions on Knowledge and Data Engineering (1 paper)Proceedings of the 31st ACM International Conference on Information & Knowledge Management (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (5 papers)Application of Statistics and Management (1 paper)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Qing Da
16 papers receiving 412 citations
Peers
Comparison fields: 5 of 58
- Management Science and Operations Research 156
- Information Systems 213
- Artificial Intelligence 262
- Computer Vision and Pattern Recognition 77
- Computer Science Applications 16
Countries citing papers authored by Qing Da
This map shows the geographic impact of Qing Da'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 Qing Da with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qing Da more than expected).
Fields of papers citing papers by Qing Da
This network shows the impact of papers produced by Qing Da. 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 Qing Da. The network helps show where Qing Da may publish in the future.
Co-authors
The 23 scholars most cited alongside Qing Da, 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 | 2018 | 95 | |
| 2 | 2018 | 88 | |
| 3 | 2019 | 87 | |
| 4 | 2014 | 59 | |
| 5 | 2020 | 50 | |
| 6 | 2018 | 14 | |
| 7 | 2021 | 13 | |
| 8 | 2022 | 6 | |
| 9 | 2019 | 4 | |
| 10 | 2022 | 4 | |
| 11 | 2014 | 2 | |
| 12 | 2020 | 2 | |
| 13 | Expected utility model based on fuzzy prior probability | 2002 | 1 |
| 14 | Non-parameter Regression Model of Traffic Flow | 2003 | 1 |
| 15 | 2021 | 1 | |
| 16 | 2022 | 1 |
About Qing Da
Qing Da is a scholar working on Artificial Intelligence, Information Systems, Management Science and Operations Research, Computer Networks and Communications and Marketing, having authored 16 papers that have together received 428 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (6 papers), Data Stream Mining Techniques (5 papers), Recommender Systems and Techniques (4 papers), Advanced Bandit Algorithms Research (3 papers), Machine Learning and Data Classification (3 papers), Optimization and Search Problems (2 papers), Consumer Market Behavior and Pricing (2 papers) and Advanced Decision-Making Techniques (2 papers). The work is most often cited by research in Management Science and Operations Research (156 citations), Information Systems (213 citations), Artificial Intelligence (262 citations), Computer Vision and Pattern Recognition (77 citations) and Computer Science Applications (16 citations). Qing Da has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Anxiang Zeng, Yang Yu, Shiyong Chen, Zhi‐Hua Zhou, Yu Yang, Yujing Hu, Yinghui Xu, Jing-Cheng Shi, Jun Tan and Lijun Zhang. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Knowledge and Data Engineering, Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Proceedings of the AAAI Conference on Artificial Intelligence and Application of Statistics and Management.
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.