Minh C. Phan
Impact in
- Artificial Intelligence top 10%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Graph Neural Networks
- Advanced Text Analysis Techniques
- Text and Document Classification Technologies
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- Data Quality and Management
Papers in
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- Topic Modeling 7
- Natural Language Processing Techniques 6
- Text and Document Classification Technologies 2
- Advanced Graph Neural Networks 1
- Bayesian Modeling and Causal Inference 1
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- Data Quality and Management 3
- Co-authors
- Yi Tay (6 shared papers)Aixin Sun (7 shared papers)Luu Anh Tuan (2 shared papers)Siu Cheung Hui (2 shared papers)Jialong Han (3 shared papers)Chenliang Li (2 shared papers)Wayne Xin Zhao (1 shared paper)Gao Cong (1 shared paper)
- Journals
- IEEE Transactions on Knowledge and Data Engineering (2 papers)Journal of the Association for Information Science and Technology (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
In The Last Decade
Minh C. Phan
9 papers receiving 188 citations
Peers
Comparison fields: 5 of 24
- Artificial Intelligence 191
- Management Science and Operations Research 33
- Information Systems 42
- Computer Science Applications 6
- Geography, Planning and Development 6
Countries citing papers authored by Minh C. Phan
This map shows the geographic impact of Minh C. Phan'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 Minh C. Phan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Minh C. Phan more than expected).
Fields of papers citing papers by Minh C. Phan
This network shows the impact of papers produced by Minh C. Phan. 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 Minh C. Phan. The network helps show where Minh C. Phan may publish in the future.
Co-authors
The 9 scholars most cited alongside Minh C. Phan, 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 | 64 | |
| 2 | 2017 | 39 | |
| 3 | 2018 | 27 | |
| 4 | 2019 | 26 | |
| 5 | 2017 | 25 | |
| 6 | 2017 | 10 | |
| 7 | 2019 | 6 | |
| 8 | 2017 | 4 | |
| 9 | 2018 | 3 |
About Minh C. Phan
Minh C. Phan is a scholar working on Artificial Intelligence, Management Science and Operations Research, Information Systems, Molecular Biology and Statistical and Nonlinear Physics, having authored 9 papers that have together received 204 indexed citations. Recurring topics across this work include Topic Modeling (7 papers), Natural Language Processing Techniques (6 papers), Data Quality and Management (3 papers), Text and Document Classification Technologies (2 papers), Complex Network Analysis Techniques (1 paper), Expert finding and Q&A systems (1 paper), Advanced Graph Neural Networks (1 paper) and Bayesian Modeling and Causal Inference (1 paper). The work is most often cited by research in Artificial Intelligence (191 citations), Management Science and Operations Research (33 citations), Information Systems (42 citations), Computer Science Applications (6 citations) and Geography, Planning and Development (6 citations). Minh C. Phan has collaborated with scholars based in Singapore and China. Frequent co-authors include Yi Tay, Aixin Sun, Luu Anh Tuan, Siu Cheung Hui, Jialong Han, Chenliang Li, Wayne Xin Zhao, Gao Cong and Zongcheng Ji. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Journal of the Association for Information Science and Technology and Proceedings of the AAAI Conference on Artificial Intelligence.
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.