Ming-Kun Xie
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Information Systems top 10%
- Molecular Biology
- Computational Theory and Mathematics
- Co-authors
- Sheng-Jun HuangShao-Yuan LiGang NiuLei FengSongcan ChenMasashi SugiyamaHaifeng ZhaoDengdi Sun
- Topics
- Text and Document Classification Technologies (12 papers)Machine Learning and Data Classification (6 papers)Domain Adaptation and Few-Shot Learning (3 papers)
In The Last Decade
Ming-Kun Xie
13 papers receiving 295 citations
Peers
Comparison fields: 5 of 31
- Artificial Intelligence 279
- Computer Vision and Pattern Recognition 136
- Information Systems 86
- Molecular Biology 50
- Computational Theory and Mathematics 17
Countries citing papers authored by Ming-Kun Xie
This map shows the geographic impact of Ming-Kun Xie'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-Kun Xie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming-Kun Xie more than expected).
Fields of papers citing papers by Ming-Kun Xie
This network shows the impact of papers produced by Ming-Kun Xie. 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-Kun Xie. The network helps show where Ming-Kun Xie may publish in the future.
Co-authorship network of co-authors of Ming-Kun Xie
This figure shows the co-authorship network connecting the top 25 collaborators of Ming-Kun Xie. A scholar is included among the top collaborators of Ming-Kun Xie based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ming-Kun Xie. Ming-Kun Xie is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 5 | |
| 8 | 10 | |
| 9 | 18 | |
| 10 | Multi-Label Learning with Pairwise Relevance Ordering | 1 |
| 11 | 17 | |
| 12 | 87 | |
| 13 | 28 | |
| 14 | 12 | |
| 15 | 11 | |
| 16 | 110 |
About Ming-Kun Xie
Ming-Kun Xie is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems, having authored 16 papers that have together received 303 indexed citations. Recurring topics across this work include Text and Document Classification Technologies (12 papers), Machine Learning and Data Classification (6 papers) and Domain Adaptation and Few-Shot Learning (3 papers). The work is most often cited by research in Artificial Intelligence (279 citations), Computer Vision and Pattern Recognition (136 citations) and Information Systems (86 citations). Ming-Kun Xie has collaborated with scholars based in China, Singapore and Japan. Frequent co-authors include Sheng-Jun Huang, Shao-Yuan Li, Gang Niu, Lei Feng, Songcan Chen, Masashi Sugiyama, Haifeng Zhao, Dengdi Sun, Shuo Xu and Leilei Ma. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Knowledge and Data Engineering and Journal of Computer Science and Technology.
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.