Yi Cai
Impact in
- Artificial Intelligence top 5%
- Topic Modeling
- Sentiment Analysis and Opinion Mining
- Advanced Text Analysis Techniques
- Text and Document Classification Technologies
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- Stock Market Forecasting Methods
Papers in
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- Topic Modeling 14
- Advanced Text Analysis Techniques 14
- Text and Document Classification Technologies 11
- Sentiment Analysis and Opinion Mining 7
- Reinforcement Learning in Robotics 4
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- Recommender Systems and Techniques 10
- Co-authors
- Haoran Xie (16 shared papers)Qing Li (12 shared papers)Ho-fung Leung (12 shared papers)Huaqing Min (11 shared papers)Jingyun Xu (5 shared papers)Dongping Huang (4 shared papers)Xiaotie Deng (1 shared paper)Jingjing Cao (1 shared paper)
In The Last Decade
Yi Cai
51 papers receiving 797 citations
Peers
Comparison fields: 5 of 110
- Artificial Intelligence 420
- Management Science and Operations Research 142
- Information Systems 203
- Statistical and Nonlinear Physics 60
- Instrumentation 15
Countries citing papers authored by Yi Cai
This map shows the geographic impact of Yi Cai'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 Yi Cai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yi Cai more than expected).
Fields of papers citing papers by Yi Cai
This network shows the impact of papers produced by Yi Cai. 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 Yi Cai. The network helps show where Yi Cai may publish in the future.
Co-authors
The 25 scholars most cited alongside Yi Cai, 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 58 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 118 | |
| 2 | 2019 | 62 | |
| 3 | 2021 | 43 | |
| 4 | 2014 | 40 | |
| 5 | 2017 | 37 | |
| 6 | 2017 | 37 | |
| 7 | 2019 | 37 | |
| 8 | 2018 | 35 | |
| 9 | 2016 | 31 | |
| 10 | 2014 | 28 | |
| 11 | 2016 | 26 | |
| 12 | 2023 | 25 | |
| 13 | 2016 | 25 | |
| 14 | 2019 | 23 | |
| 15 | 2019 | 22 | |
| 16 | 2021 | 20 | |
| 17 | 2012 | 18 | |
| 18 | 2024 | 18 | |
| 19 | 2020 | 17 | |
| 20 | 2019 | 14 |
About Yi Cai
Yi Cai is a scholar working on Artificial Intelligence, Information Systems, Management Science and Operations Research, Statistical and Nonlinear Physics and Computer Networks and Communications, having authored 58 papers that have together received 816 indexed citations. Recurring topics across this work include Topic Modeling (14 papers), Advanced Text Analysis Techniques (14 papers), Text and Document Classification Technologies (11 papers), Recommender Systems and Techniques (10 papers), Sentiment Analysis and Opinion Mining (7 papers), Complex Network Analysis Techniques (6 papers), Reinforcement Learning in Robotics (4 papers) and Data Management and Algorithms (3 papers). The work is most often cited by research in Artificial Intelligence (420 citations), Management Science and Operations Research (142 citations), Information Systems (203 citations), Statistical and Nonlinear Physics (60 citations) and Instrumentation (15 citations). Yi Cai has collaborated with scholars based in China, Hong Kong and Canada. Frequent co-authors include Haoran Xie, Qing Li, Ho-fung Leung, Huaqing Min, Jingyun Xu, Dongping Huang, Xiaotie Deng, Jingjing Cao, Ran Wang and Xiaodong Li. Their work appears in journals such as Neurocomputing, Neural Networks, International Journal of Machine Learning and Cybernetics, Engineering Applications of Artificial Intelligence and Internet 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.