Mingyun Gu
Impact in
- Artificial Intelligence top 1%
- Imbalanced Data Classification Techniques
- Anomaly Detection Techniques and Applications
- Text and Document Classification Technologies
- Machine Learning and Data Classification
-
- Artificial Intelligence in Healthcare
Papers in
-
- Sentiment Analysis and Opinion Mining 2
-
- Vehicle Routing Optimization Methods 3
- Advanced Manufacturing and Logistics Optimization 2
- Co-authors
- Haixiang Guo (10 shared papers)Yijing Li (2 shared papers)Jennifer Shang (1 shared paper)Bing Gong (1 shared paper)Linfei Chen (3 shared papers)Yuying Yang (2 shared papers)Xiaoling Ke (1 shared paper)Xiao Liu (1 shared paper)
- Journals
- Computers & Geosciences (1 paper)Applied Soft Computing (1 paper)Resources Policy (1 paper)International Journal of Environmental Research and Public Health (1 paper)Knowledge-Based Systems (1 paper)
- Partner nations
- ChinaUnited StatesSpain
In The Last Decade
Mingyun Gu
10 papers receiving 1.9k citations
Mingyun Gu's Hit Papers
Peers
Comparison fields: 5 of 160
- Artificial Intelligence 1.1k
- Health Information Management 150
- Accounting 165
- Health Informatics 15
- Media Technology 90
Countries citing papers authored by Mingyun Gu
This map shows the geographic impact of Mingyun Gu'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 Mingyun Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingyun Gu more than expected).
Fields of papers citing papers by Mingyun Gu
This network shows the impact of papers produced by Mingyun Gu. 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 Mingyun Gu. The network helps show where Mingyun Gu may publish in the future.
Co-authors
The 17 scholars most cited alongside Mingyun Gu, 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 | Learning from class-imbalanced data: Review of methods and applications Hit paper breakdown → | 2016 | 1595 |
| 2 | 2019 | 158 | |
| 3 | 2018 | 70 | |
| 4 | 2021 | 50 | |
| 5 | 2020 | 23 | |
| 6 | 2022 | 18 | |
| 7 | 2021 | 13 | |
| 8 | 2021 | 9 | |
| 9 | 2020 | 7 | |
| 10 | 2021 | 5 |
About Mingyun Gu
Mingyun Gu is a scholar working on Artificial Intelligence, Industrial and Manufacturing Engineering, Communication, Statistical and Nonlinear Physics and Building and Construction, having authored 10 papers that have together received 1.9k indexed citations. Recurring topics across this work include Vehicle Routing Optimization Methods (3 papers), Sentiment Analysis and Opinion Mining (2 papers), Advanced Manufacturing and Logistics Optimization (2 papers), Facility Location and Emergency Management (2 papers), Public Relations and Crisis Communication (2 papers), Complex Network Analysis Techniques (1 paper), Electricity Theft Detection Techniques (1 paper) and Environmental Impact and Sustainability (1 paper). The work is most often cited by research in Artificial Intelligence (1.1k citations), Health Information Management (150 citations), Accounting (165 citations), Health Informatics (15 citations) and Media Technology (90 citations). Mingyun Gu has collaborated with scholars based in China, United States and Spain. Frequent co-authors include Haixiang Guo, Yijing Li, Jennifer Shang, Bing Gong, Linfei Chen, Yuying Yang, Xiaoling Ke, Xiao Liu, Qingpeng Zhang and Jianying Yang. Their work appears in journals such as Computers & Geosciences, Applied Soft Computing, Resources Policy, International Journal of Environmental Research and Public Health and Knowledge-Based Systems.
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.