Bin Cao
- Information Systems top 0.5%
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Management Science and Operations Research top 2%
- Transportation top 2%
- Co-authors
- Qiang YangNathan N. LiuMartin ScholzRong PanRajan M. LukoseY. ZhouVincent W. ZhengYu Zheng
- Topics
- Recommender Systems and Techniques (9 papers)Text and Document Classification Technologies (5 papers)Domain Adaptation and Few-Shot Learning (4 papers)
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Bin Cao
29 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 100
- Information Systems 912
- Artificial Intelligence 691
- Computer Vision and Pattern Recognition 382
- Management Science and Operations Research 228
- Transportation 216
Countries citing papers authored by Bin Cao
This map shows the geographic impact of Bin Cao'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 Bin Cao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bin Cao more than expected).
Fields of papers citing papers by Bin Cao
This network shows the impact of papers produced by Bin Cao. 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 Bin Cao. The network helps show where Bin Cao may publish in the future.
Co-authorship network of co-authors of Bin Cao
This figure shows the co-authorship network connecting the top 25 collaborators of Bin Cao. A scholar is included among the top collaborators of Bin Cao 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 Bin Cao. Bin Cao 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 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 2 | |
| 9 | 6 | |
| 10 | 2 | |
| 11 | 69 | |
| 12 | Encoding Low-Rank and Sparse Structures Simultaneously in Multi-task Learning | 10 |
| 13 | 13 | |
| 14 | 13 | |
| 15 | Transfer Learning for Collective Link Prediction in Multiple Heterogenous Domains | 83 |
| 16 | 33 | |
| 17 | 8 | |
| 18 | One-Class Collaborative Filteringbreakdown → | 682 |
| 19 | Detect and track latent factors with online nonnegative matrix factorization | 59 |
| 20 | 64 |
About Bin Cao
Bin Cao is a scholar working on Information Systems, Artificial Intelligence and Computer Science Applications, having authored 36 papers that have together received 1.5k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (9 papers), Text and Document Classification Technologies (5 papers) and Domain Adaptation and Few-Shot Learning (4 papers). The work is most often cited by research in Computational Mathematics (66 citations), Information Systems (912 citations) and Transportation (216 citations). Bin Cao has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Qiang Yang, Nathan N. Liu, Martin Scholz, Rong Pan, Rajan M. Lukose, Y. Zhou, Vincent W. Zheng, Yu Zheng, Xing Xie and Dit‐Yan Yeung. Their work appears in journals such as Small, Advanced Science and Signal Transduction and Targeted Therapy.
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.