Yangqiu Song
- Artificial Intelligence top 0.1%
- Computer Vision and Pattern Recognition top 0.5%
- Information Systems top 0.5%
- Statistical and Nonlinear Physics top 1%
- Signal Processing top 1%
- Co-authors
- Changshui ZhangShi‐Xia LiuDan RothHaixun WangHuan ZhaoDik Lun LeeWen-Yen ChenChih‐Jen Lin
- Topics
- Topic Modeling (92 papers)Natural Language Processing Techniques (56 papers)Advanced Graph Neural Networks (45 papers)
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionStatistical and Nonlinear Physics
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceExpert Systems with ApplicationsPattern Recognition
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Yangqiu Song
198 papers receiving 5.5k citations
Hit Papers
Peers
Comparison fields: 5 of 153
- Artificial Intelligence 4.1k
- Computer Vision and Pattern Recognition 1.8k
- Information Systems 1.2k
- Statistical and Nonlinear Physics 776
- Signal Processing 555
Countries citing papers authored by Yangqiu Song
This map shows the geographic impact of Yangqiu Song'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 Yangqiu Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yangqiu Song more than expected).
Fields of papers citing papers by Yangqiu Song
This network shows the impact of papers produced by Yangqiu Song. 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 Yangqiu Song. The network helps show where Yangqiu Song may publish in the future.
Co-authorship network of co-authors of Yangqiu Song
This figure shows the co-authorship network connecting the top 25 collaborators of Yangqiu Song. A scholar is included among the top collaborators of Yangqiu Song 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 Yangqiu Song. Yangqiu Song 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 | 0 | |
| 4 | 7 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 6 | |
| 9 | 4 | |
| 10 | 1 | |
| 11 | 5 | |
| 12 | 1 | |
| 13 | 2 | |
| 14 | 3 | |
| 15 | 10 | |
| 16 | 3 | |
| 17 | 6 | |
| 18 | 65 | |
| 19 | Cross-lingual dataless classification for many languages | 11 |
| 20 | Spectral label refinement for noisy and missing text labels | 5 |
About Yangqiu Song
Yangqiu Song is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Mathematics, having authored 221 papers that have together received 5.7k indexed citations. Recurring topics across this work include Topic Modeling (92 papers), Natural Language Processing Techniques (56 papers) and Advanced Graph Neural Networks (45 papers). The work is most often cited by research in Artificial Intelligence (4.1k citations), Computer Vision and Pattern Recognition (1.8k citations) and Statistical and Nonlinear Physics (776 citations). Yangqiu Song has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Changshui Zhang, Shi‐Xia Liu, Dan Roth, Haixun Wang, Huan Zhao, Dik Lun Lee, Wen-Yen Chen, Chih‐Jen Lin, Hongjie Bai and Edward Yi Chang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Expert Systems with Applications and Pattern Recognition.
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.