Shangsong Liang
- Artificial Intelligence top 1%
- Information Systems top 0.5%
- Computer Vision and Pattern Recognition top 5%
- Statistical and Nonlinear Physics top 2%
- Management Science and Operations Research top 5%
- Co-authors
- Maarten de RijkeZaiqiao MengZhaochun RenEmine YılmazXiangliang ZhangEvangelos KanoulasFei CaiPiji Li
- Topics
- Topic Modeling (35 papers)Recommender Systems and Techniques (27 papers)Advanced Graph Neural Networks (24 papers)
- Partner nations
- ChinaUnited KingdomUnited Arab Emirates
In The Last Decade
Shangsong Liang
88 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 96
- Artificial Intelligence 1.1k
- Information Systems 838
- Computer Vision and Pattern Recognition 292
- Statistical and Nonlinear Physics 255
- Management Science and Operations Research 131
Countries citing papers authored by Shangsong Liang
This map shows the geographic impact of Shangsong Liang'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 Shangsong Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shangsong Liang more than expected).
Fields of papers citing papers by Shangsong Liang
This network shows the impact of papers produced by Shangsong Liang. 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 Shangsong Liang. The network helps show where Shangsong Liang may publish in the future.
Co-authorship network of co-authors of Shangsong Liang
This figure shows the co-authorship network connecting the top 25 collaborators of Shangsong Liang. A scholar is included among the top collaborators of Shangsong Liang 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 Shangsong Liang. Shangsong Liang 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 | 1 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 10 | |
| 8 | 4 | |
| 9 | 1 | |
| 10 | 2 | |
| 11 | 1 | |
| 12 | 1 | |
| 13 | 3 | |
| 14 | 7 | |
| 15 | 2 | |
| 16 | 1 | |
| 17 | 32 | |
| 18 | Variational Continual Bayesian Meta-Learning | 5 |
| 19 | Structure-Aware Random Fourier Kernel for Graphs | 3 |
| 20 | Fusion and diversification in information retrieval | 0 |
About Shangsong Liang
Shangsong Liang is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition, having authored 98 papers that have together received 1.6k indexed citations. Recurring topics across this work include Topic Modeling (35 papers), Recommender Systems and Techniques (27 papers) and Advanced Graph Neural Networks (24 papers). The work is most often cited by research in Information Systems (838 citations), Artificial Intelligence (1.1k citations) and Statistical and Nonlinear Physics (255 citations). Shangsong Liang has collaborated with scholars based in China, United Kingdom and United Arab Emirates. Frequent co-authors include Maarten de Rijke, Zaiqiao Meng, Zhaochun Ren, Emine Yılmaz, Xiangliang Zhang, Evangelos Kanoulas, Fei Cai, Piji Li, Teng Xiao and Shuaiqiang Wang. Their work appears in journals such as Scientific Reports, Expert Systems with Applications and IEEE Access.
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.