Phuc Do
Impact in
- Artificial Intelligence top 5%
- Topic Modeling
- Advanced Graph Neural Networks
- Sentiment Analysis and Opinion Mining
- Advanced Text Analysis Techniques
- Text and Document Classification Technologies
- Natural Language Processing Techniques
- Information Systems top 5%
- Recommender Systems and Techniques
Papers in
-
- Topic Modeling 26
- Advanced Graph Neural Networks 24
- Advanced Text Analysis Techniques 19
- Text and Document Classification Technologies 11
- Sentiment Analysis and Opinion Mining 10
- Natural Language Processing Techniques 9
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- Complex Network Analysis Techniques 22
- Co-authors
- Phu Pham (15 shared papers)Brij Bhooshan Gupta (2 shared papers)Minh Thanh Vo (1 shared paper)Thuc Dinh Nguyen (5 shared papers)Tri‐Hai Nguyen (1 shared paper)Phuong Thi-Bich Le (1 shared paper)
In The Last Decade
Phuc Do
58 papers receiving 356 citations
Peers
Comparison fields: 5 of 58
- Artificial Intelligence 294
- Information Systems 118
- Statistical and Nonlinear Physics 55
- General Social Sciences 14
- Computer Vision and Pattern Recognition 44
Countries citing papers authored by Phuc Do
This map shows the geographic impact of Phuc Do'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 Phuc Do with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Phuc Do more than expected).
Fields of papers citing papers by Phuc Do
This network shows the impact of papers produced by Phuc Do. 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 Phuc Do. The network helps show where Phuc Do may publish in the future.
Co-authors
The 6 scholars most cited alongside Phuc Do, 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 68 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 61 | |
| 2 | 2016 | 34 | |
| 3 | 2021 | 33 | |
| 4 | 2019 | 23 | |
| 5 | 2012 | 20 | |
| 6 | 2020 | 17 | |
| 7 | 2020 | 11 | |
| 8 | 2018 | 11 | |
| 9 | 2021 | 11 | |
| 10 | 2013 | 10 | |
| 11 | 2021 | 10 | |
| 12 | 2022 | 9 | |
| 13 | 2018 | 9 | |
| 14 | 2023 | 8 | |
| 15 | 2020 | 8 | |
| 16 | 2019 | 6 | |
| 17 | 2020 | 6 | |
| 18 | 2021 | 6 | |
| 19 | 2018 | 6 | |
| 20 | 2014 | 6 |
About Phuc Do
Phuc Do is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Information Systems, Computer Vision and Pattern Recognition and Signal Processing, having authored 68 papers that have together received 386 indexed citations. Recurring topics across this work include Topic Modeling (26 papers), Advanced Graph Neural Networks (24 papers), Complex Network Analysis Techniques (22 papers), Advanced Text Analysis Techniques (19 papers), Web Data Mining and Analysis (11 papers), Text and Document Classification Technologies (11 papers), Sentiment Analysis and Opinion Mining (10 papers) and Natural Language Processing Techniques (9 papers). The work is most often cited by research in Artificial Intelligence (294 citations), Information Systems (118 citations), Statistical and Nonlinear Physics (55 citations), General Social Sciences (14 citations) and Computer Vision and Pattern Recognition (44 citations). Phuc Do has collaborated with scholars based in Vietnam, Myanmar and Poland. Frequent co-authors include Phu Pham, Brij Bhooshan Gupta, Minh Thanh Vo, Thuc Dinh Nguyen, Tri‐Hai Nguyen and Phuong Thi-Bich Le. Their work appears in journals such as Neural Computing and Applications, Knowledge and Information Systems, International Journal of Machine Learning and Cybernetics, Journal of Intelligent & Fuzzy Systems and Applied 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.