Chiao-Ting Chen
Impact in
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- Stock Market Forecasting Methods
- Artificial Intelligence top 10%
- Advanced Graph Neural Networks
- Topic Modeling
Papers in
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- Stock Market Forecasting Methods 10
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- Recommender Systems and Techniques 13
- Co-authors
- Szu-Hao Huang (27 shared papers)Chi Lee (4 shared papers)An‐Pin Chen (1 shared paper)Minyou Chen (1 shared paper)Wen-Chih Peng (1 shared paper)Yuying Chen (1 shared paper)Ju-Chun Huang (2 shared papers)Yi‐Cheng Huang (1 shared paper)
- Journals
- Applied Soft Computing (4 papers)ACM Transactions on Intelligent Systems and Technology (3 papers)IEEE Access (3 papers)ACM Transactions on Knowledge Discovery from Data (2 papers)Information Fusion (2 papers)
- Partner nations
- Taiwan
In The Last Decade
Chiao-Ting Chen
23 papers receiving 398 citations
Peers
Comparison fields: 5 of 59
- Management Science and Operations Research 133
- Artificial Intelligence 175
- Information Systems 118
- Finance 42
- Economics and Econometrics 91
Countries citing papers authored by Chiao-Ting Chen
This map shows the geographic impact of Chiao-Ting Chen'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 Chiao-Ting Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chiao-Ting Chen more than expected).
Fields of papers citing papers by Chiao-Ting Chen
This network shows the impact of papers produced by Chiao-Ting Chen. 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 Chiao-Ting Chen. The network helps show where Chiao-Ting Chen may publish in the future.
Co-authors
The 8 scholars most cited alongside Chiao-Ting Chen, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 75 | |
| 2 | 2022 | 35 | |
| 3 | 2022 | 35 | |
| 4 | 2022 | 30 | |
| 5 | 2021 | 28 | |
| 6 | 2021 | 26 | |
| 7 | 2021 | 23 | |
| 8 | 2018 | 20 | |
| 9 | 2023 | 18 | |
| 10 | 2023 | 18 | |
| 11 | 2023 | 16 | |
| 12 | 2021 | 15 | |
| 13 | 2024 | 14 | |
| 14 | 2022 | 13 | |
| 15 | 2023 | 10 | |
| 16 | 2023 | 9 | |
| 17 | 2024 | 8 | |
| 18 | 2023 | 6 | |
| 19 | 2024 | 4 | |
| 20 | 2025 | 3 |
About Chiao-Ting Chen
Chiao-Ting Chen is a scholar working on Management Science and Operations Research, Information Systems, Artificial Intelligence, Finance and Economics and Econometrics, having authored 27 papers that have together received 411 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (13 papers), Stock Market Forecasting Methods (10 papers), Advanced Graph Neural Networks (8 papers), Financial Markets and Investment Strategies (5 papers), Topic Modeling (5 papers), Complex Systems and Time Series Analysis (4 papers), Energy Load and Power Forecasting (3 papers) and Market Dynamics and Volatility (3 papers). The work is most often cited by research in Management Science and Operations Research (133 citations), Artificial Intelligence (175 citations), Information Systems (118 citations), Finance (42 citations) and Economics and Econometrics (91 citations). Chiao-Ting Chen has collaborated with scholars based in Taiwan. Frequent co-authors include Szu-Hao Huang, Chi Lee, An‐Pin Chen, Minyou Chen, Wen-Chih Peng, Yuying Chen, Ju-Chun Huang and Yi‐Cheng Huang. Their work appears in journals such as Applied Soft Computing, ACM Transactions on Intelligent Systems and Technology, IEEE Access, ACM Transactions on Knowledge Discovery from Data and Information Fusion.
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.