Bin Cao

2.2k total citations · 1 hit paper
36 papers, 1.5k citations indexed

About

Bin Cao is a scholar working on Artificial Intelligence, Information Systems and Molecular Biology. According to data from OpenAlex, Bin Cao has authored 36 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 12 papers in Information Systems and 7 papers in Molecular Biology. Recurrent topics in Bin Cao's work include Recommender Systems and Techniques (9 papers), Text and Document Classification Technologies (5 papers) and Domain Adaptation and Few-Shot Learning (4 papers). Bin Cao is often cited by papers focused on Recommender Systems and Techniques (9 papers), Text and Document Classification Technologies (5 papers) and Domain Adaptation and Few-Shot Learning (4 papers). Bin Cao collaborates with scholars based in China, Hong Kong and United States. Bin Cao's 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 and has published in prestigious journals such as Small, Advanced Science and Signal Transduction and Targeted Therapy.

In The Last Decade

Bin Cao

29 papers receiving 1.4k citations

Hit Papers

One-Class Collaborative Filtering 2008 2026 2014 2020 2008 200 400 600

Peers

Bin Cao
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
Replace Javed A. Aslam with:
Javed A. Aslam United States
Shoujin Wang China
Lianghao Xia Hong Kong
Lei Zhao China
Lejian Liao China
Rohan Anil United States
Zhiting Hu United States
Huan Zhao China
Xu Chen China
Vihan Jain United States
Javed A. Aslam United States View profile →
Citations per field, relative to Bin Cao
Bin Cao · 1×
Citations per year, relative to Bin Cao
Bin Cao · 1×

Countries citing papers authored by Bin Cao

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

20 of 20 papers shown
# 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 Filtering breakdown →
682
19
Detect and track latent factors with online nonnegative matrix factorization
59
20 64

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.

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