Bei Shi
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 10%
- Information Systems top 10%
- Sociology and Political Science
- Computer Networks and Communications
- Co-authors
- Wai LamLidong BingXin LiWei YangDeheng YeLanxiao HuangTengfei ShiQiang Fu
- Topics
- Topic Modeling (10 papers)Natural Language Processing Techniques (6 papers)Artificial Intelligence in Games (5 papers)
- Journals
- IEEE Transactions on Neural Networks and Learning SystemsIEEE Transactions on Knowledge and Data EngineeringManagement Accounting Research
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Bei Shi
21 papers receiving 704 citations
Hit Papers
Peers
Comparison fields: 5 of 64
- Artificial Intelligence 606
- Computer Vision and Pattern Recognition 87
- Information Systems 54
- Sociology and Political Science 42
- Computer Networks and Communications 40
Countries citing papers authored by Bei Shi
This map shows the geographic impact of Bei 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 Bei Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bei Shi more than expected).
Fields of papers citing papers by Bei Shi
This network shows the impact of papers produced by Bei 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 Bei Shi. The network helps show where Bei Shi may publish in the future.
Co-authorship network of co-authors of Bei Shi
This figure shows the co-authorship network connecting the top 25 collaborators of Bei Shi. A scholar is included among the top collaborators of Bei 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 Bei Shi. Bei 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 | 2 | |
| 2 | 3 | |
| 3 | 4 | |
| 4 | 11 | |
| 5 | 28 | |
| 6 | 1 | |
| 7 | 27 | |
| 8 | 2 | |
| 9 | 185 | |
| 10 | 18 | |
| 11 | 2 | |
| 12 | DHER: Hindsight Experience Replay for Dynamic Goals | 33 |
| 13 | 2 | |
| 14 | Transformation Networks for Target-Oriented Sentiment Classificationbreakdown → | 341 |
| 15 | 18 | |
| 16 | Location Based Services Recommendation with Budget Constraints. | 2 |
| 17 | 10 | |
| 18 | A unified model for unsupervised opinion spamming detection incorporating text generality | 13 |
| 19 | A Probabilistic Co-Bootstrapping Method for Entity Set Expansion | 10 |
| 20 | Audio Signal Decorrelation Based on Reciprocal-Maximal Length Sequence Filters and Its Applications to Spatial Sound | 0 |
About Bei Shi
Bei Shi is a scholar working on General Decision Sciences, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 22 papers that have together received 723 indexed citations. Recurring topics across this work include Topic Modeling (10 papers), Natural Language Processing Techniques (6 papers) and Artificial Intelligence in Games (5 papers). The work is most often cited by research in Artificial Intelligence (606 citations), Computer Vision and Pattern Recognition (87 citations) and Signal Processing (26 citations). Bei Shi has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Wai Lam, Lidong Bing, Xin Li, Wei Yang, Deheng Ye, Lanxiao Huang, Tengfei Shi, Qiang Fu, Liang Wang and Peilin Zhao. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Knowledge and Data Engineering and Management Accounting Research.
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.