Lingling Yi
Impact in
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- Complex Network Analysis Techniques
- Artificial Intelligence top 5%
- Advanced Graph Neural Networks
- Topic Modeling
- Domain Adaptation and Few-Shot Learning
Papers in
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- Recommender Systems and Techniques 12
- Web Data Mining and Analysis 1
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- Advanced Graph Neural Networks 10
- Topic Modeling 4
- Co-authors
- Yangqiu Song (1 shared paper)Chen Gao (4 shared papers)Jingtao Ding (5 shared papers)Depeng Jin (3 shared papers)Yong Li (3 shared papers)Chonggang Song (6 shared papers)Yuhan Quan (2 shared papers)Xiangnan He (1 shared paper)
In The Last Decade
Lingling Yi
14 papers receiving 292 citations
Peers
Comparison fields: 5 of 48
- Statistical and Nonlinear Physics 106
- Artificial Intelligence 208
- Information Systems 133
- Computer Vision and Pattern Recognition 65
- Management Science and Operations Research 25
Countries citing papers authored by Lingling Yi
This map shows the geographic impact of Lingling Yi'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 Lingling Yi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lingling Yi more than expected).
Fields of papers citing papers by Lingling Yi
This network shows the impact of papers produced by Lingling Yi. 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 Lingling Yi. The network helps show where Lingling Yi may publish in the future.
Co-authors
The 25 scholars most cited alongside Lingling Yi, 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 | 2018 | 137 | |
| 2 | 2023 | 44 | |
| 3 | 2022 | 40 | |
| 4 | 2023 | 13 | |
| 5 | 2024 | 12 | |
| 6 | 2022 | 12 | |
| 7 | 2022 | 10 | |
| 8 | 2018 | 9 | |
| 9 | 2023 | 7 | |
| 10 | 2023 | 7 | |
| 11 | 2023 | 3 | |
| 12 | 2025 | 1 | |
| 13 | 2018 | 1 | |
| 14 | 2022 | 1 | |
| 15 | 2025 | 0 | |
| 16 | 2023 | 0 | |
| 17 | 2025 | 0 |
About Lingling Yi
Lingling Yi is a scholar working on Information Systems, Artificial Intelligence, Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition and Management Science and Operations Research, having authored 17 papers that have together received 297 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (12 papers), Advanced Graph Neural Networks (10 papers), Complex Network Analysis Techniques (5 papers), Topic Modeling (4 papers), Advanced Bandit Algorithms Research (3 papers), Image and Video Quality Assessment (2 papers), Caching and Content Delivery (2 papers) and Web Data Mining and Analysis (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (106 citations), Artificial Intelligence (208 citations), Information Systems (133 citations), Computer Vision and Pattern Recognition (65 citations) and Management Science and Operations Research (25 citations). Lingling Yi has collaborated with scholars based in China, Hong Kong and Singapore. Frequent co-authors include Yangqiu Song, Chen Gao, Jingtao Ding, Depeng Jin, Yong Li, Chonggang Song, Yuhan Quan, Xiangnan He, Yongdong Zhang and Guohui Ling. Their work appears in journals such as ACM Transactions on Information Systems, ACM Transactions on Knowledge Discovery from Data, Information Processing & Management, IEEE Transactions on Visualization and Computer Graphics and Entropy.
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.