Liangwei Yang
Impact in
- Information Systems top 5%
- Recommender Systems and Techniques
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- Graphene research and applications
Papers in
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- Advanced Graph Neural Networks 17
- Topic Modeling 10
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- Recommender Systems and Techniques 18
- Co-authors
- Philip S. Yu (20 shared papers)Zhiwei Liu (13 shared papers)Ziwei Fan (3 shared papers)Shuao Wang (8 shared papers)Zhifang Chai (7 shared papers)Yaxing Wang (8 shared papers)Hao Peng (4 shared papers)Hui Gao (4 shared papers)
- Journals
- Inorganic Chemistry (3 papers)Angewandte Chemie International Edition (2 papers)The FASEB Journal (1 paper)IEEE Transactions on Industrial Informatics (1 paper)Neurocomputing (1 paper)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Liangwei Yang
50 papers receiving 978 citations
Liangwei Yang's Hit Papers
Peers
Comparison fields: 5 of 115
- Information Systems 188
- Materials Chemistry 348
- Statistical and Nonlinear Physics 92
- Artificial Intelligence 234
- Radiation 56
Countries citing papers authored by Liangwei Yang
This map shows the geographic impact of Liangwei Yang'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 Liangwei Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Liangwei Yang more than expected).
Fields of papers citing papers by Liangwei Yang
This network shows the impact of papers produced by Liangwei Yang. 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 Liangwei Yang. The network helps show where Liangwei Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside Liangwei Yang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Federated Social Recommendation with Graph Neural Network Hit paper breakdown → | 2022 | 124 |
| 2 | 2023 | 98 | |
| 3 | 2014 | 93 | |
| 4 | 2020 | 86 | |
| 5 | 2022 | 76 | |
| 6 | 2018 | 59 | |
| 7 | 2019 | 54 | |
| 8 | 2020 | 44 | |
| 9 | 2015 | 29 | |
| 10 | 2022 | 27 | |
| 11 | 2022 | 26 | |
| 12 | 2022 | 25 | |
| 13 | 2023 | 25 | |
| 14 | 2017 | 19 | |
| 15 | 2020 | 18 | |
| 16 | 2023 | 15 | |
| 17 | 2021 | 15 | |
| 18 | 2019 | 14 | |
| 19 | 2019 | 13 | |
| 20 | 2024 | 13 |
About Liangwei Yang
Liangwei Yang is a scholar working on Artificial Intelligence, Information Systems, Materials Chemistry, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition, having authored 63 papers that have together received 994 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (18 papers), Advanced Graph Neural Networks (17 papers), Topic Modeling (10 papers), Radiation Detection and Scintillator Technologies (5 papers), Luminescence Properties of Advanced Materials (5 papers), Graphene research and applications (5 papers), Perovskite Materials and Applications (4 papers) and Complex Network Analysis Techniques (4 papers). The work is most often cited by research in Information Systems (188 citations), Materials Chemistry (348 citations), Statistical and Nonlinear Physics (92 citations), Artificial Intelligence (234 citations) and Radiation (56 citations). Liangwei Yang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Philip S. Yu, Zhiwei Liu, Ziwei Fan, Shuao Wang, Zhifang Chai, Yaxing Wang, Hao Peng, Hui Gao, Jin Zhang and Yumin Wang. Their work appears in journals such as Inorganic Chemistry, Angewandte Chemie International Edition, The FASEB Journal, IEEE Transactions on Industrial Informatics and Neurocomputing.
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.