Ming He
Impact in
- Information Systems top 5%
- Recommender Systems and Techniques
- Artificial Intelligence top 10%
- Advanced Graph Neural Networks
- Topic Modeling
- Sentiment Analysis and Opinion Mining
Papers in
-
- Topic Modeling 11
- Advanced Graph Neural Networks 9
- Sentiment Analysis and Opinion Mining 4
-
- Recommender Systems and Techniques 16
- Co-authors
- Pinhua Rao (1 shared paper)Hongke Zhao (10 shared papers)Jianping Fan (8 shared papers)Chuang Zhao (7 shared papers)Enhong Chen (5 shared papers)Jian Zhang (1 shared paper)Yong Ge (3 shared papers)Dingyong Wang (2 shared papers)
- Journals
- IEEE Transactions on Knowledge and Data Engineering (3 papers)ACM Transactions on the Web (3 papers)IEEE Access (2 papers)Environmental Monitoring and Assessment (2 papers)Neurocomputing (2 papers)
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Ming He
47 papers receiving 555 citations
Peers
Comparison fields: 5 of 106
- Information Systems 151
- Artificial Intelligence 190
- Computer Vision and Pattern Recognition 101
- Pollution 51
- Health, Toxicology and Mutagenesis 40
Countries citing papers authored by Ming He
This map shows the geographic impact of Ming He'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 Ming He with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming He more than expected).
Fields of papers citing papers by Ming He
This network shows the impact of papers produced by Ming He. 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 Ming He. The network helps show where Ming He may publish in the future.
Co-authors
The 25 scholars most cited alongside Ming He, 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 58 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2005 | 68 | |
| 2 | 2023 | 64 | |
| 3 | 2023 | 35 | |
| 4 | 2023 | 34 | |
| 5 | 2008 | 34 | |
| 6 | 2017 | 34 | |
| 7 | 2023 | 26 | |
| 8 | 2022 | 24 | |
| 9 | 2015 | 24 | |
| 10 | 2016 | 24 | |
| 11 | 2003 | 18 | |
| 12 | 2021 | 15 | |
| 13 | 2023 | 15 | |
| 14 | 2022 | 14 | |
| 15 | 2007 | 12 | |
| 16 | 2022 | 11 | |
| 17 | 2025 | 10 | |
| 18 | 2023 | 10 | |
| 19 | 2016 | 10 | |
| 20 | 2022 | 8 |
About Ming He
Ming He is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Computer Networks and Communications and Molecular Biology, having authored 58 papers that have together received 568 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (16 papers), Topic Modeling (11 papers), Advanced Graph Neural Networks (9 papers), Caching and Content Delivery (4 papers), Sentiment Analysis and Opinion Mining (4 papers), Complex Network Analysis Techniques (4 papers), Advanced Image and Video Retrieval Techniques (3 papers) and Nuclear Physics and Applications (3 papers). The work is most often cited by research in Information Systems (151 citations), Artificial Intelligence (190 citations), Computer Vision and Pattern Recognition (101 citations), Pollution (51 citations) and Health, Toxicology and Mutagenesis (40 citations). Ming He has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Pinhua Rao, Hongke Zhao, Jianping Fan, Chuang Zhao, Enhong Chen, Jian Zhang, Yong Ge, Dingyong Wang, Shouqin Sun and Qi Liu. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, ACM Transactions on the Web, IEEE Access, Environmental Monitoring and Assessment and Neurocomputing.
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.