Fuyu Lv
Impact in
- Information Systems top 5%
- Recommender Systems and Techniques
- Artificial Intelligence top 10%
- Advanced Graph Neural Networks
- Topic Modeling
- Text and Document Classification Technologies
Papers in
-
- Recommender Systems and Techniques 7
- Web Data Mining and Analysis 2
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- Topic Modeling 4
- Advanced Graph Neural Networks 3
- Domain Adaptation and Few-Shot Learning 1
- Co-authors
- Keping Yang (2 shared papers)Quan Lin (1 shared paper)Fei Sun (1 shared paper)Wilfred Ng (1 shared paper)Xiaoyi Zeng (5 shared papers)Xiao-Ming Wu (2 shared papers)Jing Zhang (3 shared papers)Hong Wen (3 shared papers)
- Journals
- Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (1 paper)Rare & Special e-Zone (The Hong Kong University of Science and Technology) (1 paper)Proceedings of the ACM Web Conference 2022 (3 papers)Proceedings of the 31st ACM International Conference on Information & Knowledge Management (1 paper)Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (1 paper)
In The Last Decade
Fuyu Lv
9 papers receiving 195 citations
Peers
Comparison fields: 5 of 21
- Information Systems 160
- Artificial Intelligence 140
- Computer Vision and Pattern Recognition 57
- Management Science and Operations Research 34
- Transportation 11
Countries citing papers authored by Fuyu Lv
This map shows the geographic impact of Fuyu Lv'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 Fuyu Lv with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fuyu Lv more than expected).
Fields of papers citing papers by Fuyu Lv
This network shows the impact of papers produced by Fuyu Lv. 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 Fuyu Lv. The network helps show where Fuyu Lv may publish in the future.
Co-authors
The 25 scholars most cited alongside Fuyu Lv, 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 | 93 | |
| 2 | 2021 | 38 | |
| 3 | 2022 | 19 | |
| 4 | 2021 | 19 | |
| 5 | 2022 | 13 | |
| 6 | 2022 | 9 | |
| 7 | 2022 | 9 | |
| 8 | 2022 | 5 | |
| 9 | 2023 | 3 | |
| 10 | 2025 | 0 | |
| 11 | 2024 | 0 | |
| 12 | 2022 | 0 |
About Fuyu Lv
Fuyu Lv is a scholar working on Information Systems, Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications and Sociology and Political Science, having authored 12 papers that have together received 208 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (7 papers), Topic Modeling (4 papers), Advanced Image and Video Retrieval Techniques (3 papers), Advanced Graph Neural Networks (3 papers), Web Data Mining and Analysis (2 papers), Image Retrieval and Classification Techniques (2 papers), Domain Adaptation and Few-Shot Learning (1 paper) and Consumer Market Behavior and Pricing (1 paper). The work is most often cited by research in Information Systems (160 citations), Artificial Intelligence (140 citations), Computer Vision and Pattern Recognition (57 citations), Management Science and Operations Research (34 citations) and Transportation (11 citations). Fuyu Lv has collaborated with scholars based in China, Hong Kong and Australia. Frequent co-authors include Keping Yang, Quan Lin, Fei Sun, Wilfred Ng, Xiaoyi Zeng, Xiao-Ming Wu, Jing Zhang, Hong Wen, Sen Li and Qianli Ma. Their work appears in journals such as Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Rare & Special e-Zone (The Hong Kong University of Science and Technology), Proceedings of the ACM Web Conference 2022, Proceedings of the 31st ACM International Conference on Information & Knowledge Management and Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval.
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.