Yue Shi
- Information Systems top 0.2%
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 2%
- Management Science and Operations Research top 1%
- Computer Networks and Communications top 5%
- Co-authors
- Alan HanjalićMartha LarsonLinas BaltrunasAlexandros KaratzoglouNuria OliverLiangjie HongYizhou SunTing Chen
- Topics
- Recommender Systems and Techniques (28 papers)Advanced Graph Neural Networks (10 papers)Advanced Bandit Algorithms Research (10 papers)
- Partner nations
- NetherlandsChinaSpain
In The Last Decade
Yue Shi
43 papers receiving 1.9k citations
Hit Papers
Peers
Comparison fields: 5 of 95
- Information Systems 1.5k
- Artificial Intelligence 882
- Computer Vision and Pattern Recognition 570
- Management Science and Operations Research 398
- Computer Networks and Communications 264
Countries citing papers authored by Yue Shi
This map shows the geographic impact of Yue Shi'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 Yue Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yue Shi more than expected).
Fields of papers citing papers by Yue Shi
This network shows the impact of papers produced by Yue Shi. 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 Yue Shi. The network helps show where Yue Shi may publish in the future.
Co-authorship network of co-authors of Yue Shi
This figure shows the co-authorship network connecting the top 25 collaborators of Yue Shi. A scholar is included among the top collaborators of Yue Shi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yue Shi. Yue Shi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | Wheat powdery mildew monitoring based on GF-1 remote sensing image and relief-mRMR-GASVM model. | 7 |
| 5 | 2 | |
| 6 | 2 | |
| 7 | Monitoring and classification of wheat take-all in field based on imaging spectrometer. | 2 |
| 8 | 30 | |
| 9 | CLiMF: collaborative less-is-more filtering | 18 |
| 10 | 6 | |
| 11 | 10 | |
| 12 | 58 | |
| 13 | 1 | |
| 14 | 15 | |
| 15 | 43 | |
| 16 | 200 | |
| 17 | 56 | |
| 18 | 41 | |
| 19 | 4 | |
| 20 | 1 |
About Yue Shi
Yue Shi is a scholar working on Information Systems, Management Science and Operations Research and Computer Vision and Pattern Recognition, having authored 45 papers that have together received 2.0k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (28 papers), Advanced Graph Neural Networks (10 papers) and Advanced Bandit Algorithms Research (10 papers). The work is most often cited by research in Computational Mathematics (51 citations), Information Systems (1.5k citations) and Management Science and Operations Research (398 citations). Yue Shi has collaborated with scholars based in Netherlands, China and Spain. Frequent co-authors include Alan Hanjalić, Martha Larson, Linas Baltrunas, Alexandros Karatzoglou, Nuria Oliver, Martha Larson, Liangjie Hong, Yizhou Sun, Ting Chen and Yuanchun Shi. Their work appears in journals such as Circulation, ACM Computing Surveys and Information Sciences.
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.