Lingbing Guo
Impact in
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- Data Quality and Management
- Artificial Intelligence top 5%
- Advanced Graph Neural Networks
- Topic Modeling
- Natural Language Processing Techniques
- Domain Adaptation and Few-Shot Learning
- Semantic Web and Ontologies
Papers in
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- Advanced Graph Neural Networks 9
- Topic Modeling 9
- Domain Adaptation and Few-Shot Learning 3
- Natural Language Processing Techniques 2
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- Multimodal Machine Learning Applications 4
- Co-authors
- Wei Hu (4 shared papers)Zequn Sun (4 shared papers)Qinghe Zhang (2 shared papers)Yuzhong Qu (2 shared papers)Muhao Chen (1 shared paper)Huajun Chen (5 shared papers)Zhuo Chen (6 shared papers)Yajing Xu (3 shared papers)
- Journals
- Information Fusion (1 paper)Data Intelligence (1 paper)Knowledge-Based Systems (1 paper)Findings of the Association for Computational Linguistics: ACL 2022 (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Lingbing Guo
11 papers receiving 292 citations
Peers
Comparison fields: 5 of 40
- Management Science and Operations Research 145
- Artificial Intelligence 289
- Statistical and Nonlinear Physics 23
- Computer Vision and Pattern Recognition 27
- Information Systems 29
Countries citing papers authored by Lingbing Guo
This map shows the geographic impact of Lingbing Guo'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 Lingbing Guo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lingbing Guo more than expected).
Fields of papers citing papers by Lingbing Guo
This network shows the impact of papers produced by Lingbing Guo. 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 Lingbing Guo. The network helps show where Lingbing Guo may publish in the future.
Co-authors
The 25 scholars most cited alongside Lingbing Guo, 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 | 2019 | 150 | |
| 2 | 2019 | 58 | |
| 3 | 2023 | 25 | |
| 4 | 2024 | 25 | |
| 5 | 2024 | 10 | |
| 6 | 2018 | 10 | |
| 7 | 2019 | 9 | |
| 8 | 2022 | 8 | |
| 9 | 2025 | 5 | |
| 10 | 2024 | 4 | |
| 11 | 2025 | 1 | |
| 12 | 2024 | 0 |
About Lingbing Guo
Lingbing Guo is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Management Science and Operations Research, Health Information Management and Information Systems, having authored 12 papers that have together received 305 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (9 papers), Topic Modeling (9 papers), Multimodal Machine Learning Applications (4 papers), Data Quality and Management (3 papers), Domain Adaptation and Few-Shot Learning (3 papers), Natural Language Processing Techniques (2 papers), Complex Network Analysis Techniques (1 paper) and Artificial Intelligence in Healthcare (1 paper). The work is most often cited by research in Management Science and Operations Research (145 citations), Artificial Intelligence (289 citations), Statistical and Nonlinear Physics (23 citations), Computer Vision and Pattern Recognition (27 citations) and Information Systems (29 citations). Lingbing Guo has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Wei Hu, Zequn Sun, Qinghe Zhang, Yuzhong Qu, Muhao Chen, Huajun Chen, Zhuo Chen, Yajing Xu, Fang Yin and Jiaoyan Chen. Their work appears in journals such as Information Fusion, Data Intelligence, Knowledge-Based Systems, Findings of the Association for Computational Linguistics: ACL 2022 and arXiv (Cornell University).
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.