Yong Yu
Impact in
- Computational Mathematics top 0.5%
- Computer Vision and Pattern Recognition top 0.05%
- Face and Expression Recognition
Papers in
-
- Recommender Systems and Techniques 83
- Web Data Mining and Analysis 34
-
- Topic Modeling 65
- Advanced Graph Neural Networks 28
- Text and Document Classification Technologies 27
- Natural Language Processing Techniques 26
- Semantic Web and Ontologies 24
Yong Yu
287 papers receiving 15.8k citations
Hit Papers
Peers
Comparison fields: 5 of 187
- Computational Mathematics 205
- Computer Vision and Pattern Recognition 6.2k
- Artificial Intelligence 9.0k
- Information Systems 4.5k
- Media Technology 1.5k
Countries citing papers authored by Yong Yu
This map shows the geographic impact of Yong Yu'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 Yong Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yong Yu more than expected).
Fields of papers citing papers by Yong Yu
This network shows the impact of papers produced by Yong Yu. 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 Yong Yu. The network helps show where Yong Yu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yong Yu, 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 | 2025 | 0 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 4 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 6 | |
| 6 | How Can Recommender Systems Benefit from Large Language Models: A Survey Hit paper breakdown → | 2024 | 53 |
| 7 | 2024 | 36 | |
| 8 | 2024 | 2 | |
| 9 | 2023 | 8 | |
| 10 | 2023 | 9 | |
| 11 | 2023 | 16 | |
| 12 | 2023 | 8 | |
| 13 | 2023 | 6 | |
| 14 | 2023 | 0 | |
| 15 | 2023 | 1 | |
| 16 | 2023 | 6 | |
| 17 | 2023 | 2 | |
| 18 | 2022 | 2 | |
| 19 | 2018 | 52 | |
| 20 | Learning to Generate Semantic Annotation for Domain Specific Sentences. | 2001 | 21 |
About Yong Yu
Yong Yu is a scholar working on Information Systems, Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Science Applications and Signal Processing, having authored 301 papers that have together received 16.5k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (83 papers), Topic Modeling (65 papers), Web Data Mining and Analysis (34 papers), Advanced Graph Neural Networks (28 papers), Text and Document Classification Technologies (27 papers), Advanced Image and Video Retrieval Techniques (27 papers), Natural Language Processing Techniques (26 papers) and Semantic Web and Ontologies (24 papers). The work is most often cited by research in Computational Mathematics (205 citations), Computer Vision and Pattern Recognition (6.2k citations), Artificial Intelligence (9.0k citations), Information Systems (4.5k citations) and Media Technology (1.5k citations). Yong Yu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Weinan Zhang, Gui-Rong Xue, Zhouchen Lin, Guangcan Liu, Qiang Yang, Wenyuan Dai, Yi Ma, Shuicheng Yan, Ju Sun and Jun Wang. Their work appears in journals such as IEEE Access, ACM Transactions on Information Systems, IEEE Transactions on Knowledge and Data Engineering, Information Processing & Management and Frontiers of Computer Science.
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.