Zhanqiu Zhang
- Artificial Intelligence top 5%
- Management Science and Operations Research top 10%
- Computer Vision and Pattern Recognition
- Statistical and Nonlinear Physics top 10%
- Information Systems
- Co-authors
- Jie WangYongdong ZhangFeng WuJieping YeHuarui He
- Topics
- Advanced Graph Neural Networks (5 papers)Topic Modeling (4 papers)Graph Theory and Algorithms (2 papers)
- Cited by
- Artificial IntelligenceManagement Science and Operations ResearchStatistical and Nonlinear Physics
- Journals
- Proceedings of the ACM Web Conference 2022Neural Information Processing SystemsProceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
- Partner nations
- China
In The Last Decade
Zhanqiu Zhang
5 papers receiving 315 citations
Hit Papers
Peers
Comparison fields: 5 of 40
- Artificial Intelligence 300
- Management Science and Operations Research 71
- Computer Vision and Pattern Recognition 47
- Statistical and Nonlinear Physics 43
- Information Systems 42
Countries citing papers authored by Zhanqiu Zhang
This map shows the geographic impact of Zhanqiu Zhang'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 Zhanqiu Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhanqiu Zhang more than expected).
Fields of papers citing papers by Zhanqiu Zhang
This network shows the impact of papers produced by Zhanqiu Zhang. 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 Zhanqiu Zhang. The network helps show where Zhanqiu Zhang may publish in the future.
Co-authorship network of co-authors of Zhanqiu Zhang
This figure shows the co-authorship network connecting the top 25 collaborators of Zhanqiu Zhang. A scholar is included among the top collaborators of Zhanqiu Zhang 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 Zhanqiu Zhang. Zhanqiu Zhang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 23 | |
| 2 | 51 | |
| 3 | 7 | |
| 4 | Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion | 2 |
| 5 | Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Predictionbreakdown → | 241 |
About Zhanqiu Zhang
Zhanqiu Zhang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Management Science and Operations Research, having authored 5 papers that have together received 324 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (5 papers), Topic Modeling (4 papers) and Graph Theory and Algorithms (2 papers). The work is most often cited by research in Artificial Intelligence (300 citations), Management Science and Operations Research (71 citations) and Statistical and Nonlinear Physics (43 citations). Zhanqiu Zhang has collaborated with scholars based in China. Frequent co-authors include Jie Wang, Yongdong Zhang, Feng Wu, Jieping Ye and Huarui He. Their work appears in journals such as Proceedings of the ACM Web Conference 2022, Neural Information Processing Systems and Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
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.