Tong Man
Impact in
- Information Systems top 2%
- Recommender Systems and Techniques
- Artificial Intelligence top 5%
- Advanced Graph Neural Networks
- Topic Modeling
- Domain Adaptation and Few-Shot Learning
Papers in
-
- Advanced Graph Neural Networks 3
- Bayesian Modeling and Causal Inference 2
-
- Recommender Systems and Techniques 3
- Data Mining Algorithms and Applications 1
- Co-authors
- Xueqi Cheng (4 shared papers)Huawei Shen (3 shared papers)Xiaolong Jin (2 shared papers)Shenghua Liu (1 shared paper)Oliver Schulte (2 shared papers)Hassan Khosravi (2 shared papers)Junming Huang (1 shared paper)Huawei Shen (1 shared paper)
- Journals
- Machine Learning (1 paper)International Joint Conference on Artificial Intelligence (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
In The Last Decade
Tong Man
6 papers receiving 429 citations
Tong Man's Hit Papers
Peers
Comparison fields: 5 of 30
- Information Systems 301
- Artificial Intelligence 366
- Statistical and Nonlinear Physics 127
- Management Science and Operations Research 63
- Computer Vision and Pattern Recognition 69
Countries citing papers authored by Tong Man
This map shows the geographic impact of Tong Man'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 Tong Man with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tong Man more than expected).
Fields of papers citing papers by Tong Man
This network shows the impact of papers produced by Tong Man. 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 Tong Man. The network helps show where Tong Man may publish in the future.
Co-authors
The 8 scholars most cited alongside Tong Man, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Cross-Domain Recommendation: An Embedding and Mapping Approach Hit paper breakdown → | 2017 | 258 |
| 2 | Predict anchor links across social networks via an embedding approach | 2016 | 143 |
| 3 | 2015 | 17 | |
| 4 | 2010 | 16 | |
| 5 | 2012 | 3 | |
| 6 | 2012 | 2 |
About Tong Man
Tong Man is a scholar working on Artificial Intelligence, Information Systems, Statistical and Nonlinear Physics, Management Science and Operations Research and Computer Networks and Communications, having authored 6 papers that have together received 439 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (3 papers), Recommender Systems and Techniques (3 papers), Complex Network Analysis Techniques (2 papers), Bayesian Modeling and Causal Inference (2 papers), Opinion Dynamics and Social Influence (2 papers), Advanced Database Systems and Queries (1 paper), Advanced Bandit Algorithms Research (1 paper) and Data Mining Algorithms and Applications (1 paper). The work is most often cited by research in Information Systems (301 citations), Artificial Intelligence (366 citations), Statistical and Nonlinear Physics (127 citations), Management Science and Operations Research (63 citations) and Computer Vision and Pattern Recognition (69 citations). Tong Man has collaborated with scholars based in China and Canada. Frequent co-authors include Xueqi Cheng, Huawei Shen, Xiaolong Jin, Shenghua Liu, Oliver Schulte, Hassan Khosravi, Junming Huang and Huawei Shen. Their work appears in journals such as Machine Learning, International Joint Conference on Artificial Intelligence and Proceedings of the AAAI Conference on Artificial Intelligence.
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.