Suyang Dai
Impact in
- Artificial Intelligence top 10%
- Topic Modeling
- Text and Document Classification Technologies
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
- Sentiment Analysis and Opinion Mining
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- Web Data Mining and Analysis
- Spam and Phishing Detection
Papers in
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- Advanced Text Analysis Techniques 3
- Topic Modeling 3
- Sentiment Analysis and Opinion Mining 2
- Natural Language Processing Techniques 2
- Text and Document Classification Technologies 2
- Speech and dialogue systems 1
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- Biomedical Text Mining and Ontologies 3
- Co-authors
- Shanfeng Zhu (5 shared papers)Hiroshi Mamitsuka (3 shared papers)Ronghui You (3 shared papers)Zihan Zhang (2 shared papers)Ziye Wang (1 shared paper)Xiaodi Huang (3 shared papers)Zhiyong Lu (1 shared paper)Wei Zhou (2 shared papers)
- Journals
- IEEE/ACM Transactions on Audio Speech and Language Processing (1 paper)IEEE/ACM Transactions on Computational Biology and Bioinformatics (1 paper)Bioinformatics (1 paper)arXiv (Cornell University) (2 papers)
In The Last Decade
Suyang Dai
7 papers receiving 118 citations
Peers
Comparison fields: 5 of 28
- Artificial Intelligence 100
- Information Systems 21
- Health Informatics 1
- Management of Technology and Innovation 3
- Computer Vision and Pattern Recognition 8
Countries citing papers authored by Suyang Dai
This map shows the geographic impact of Suyang Dai'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 Suyang Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Suyang Dai more than expected).
Fields of papers citing papers by Suyang Dai
This network shows the impact of papers produced by Suyang Dai. 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 Suyang Dai. The network helps show where Suyang Dai may publish in the future.
Co-authors
The 15 scholars most cited alongside Suyang Dai, 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 | 2018 | 46 | |
| 2 | 2019 | 26 | |
| 3 | AttentionXML: Extreme Multi-Label Text Classification with Multi-Label Attention Based Recurrent Neural Networks. | 2018 | 19 |
| 4 | 2019 | 16 | |
| 5 | 2022 | 13 | |
| 6 | 2021 | 2 | |
| 7 | 2018 | 1 |
About Suyang Dai
Suyang Dai is a scholar working on Artificial Intelligence, Molecular Biology, Experimental and Cognitive Psychology, Developmental and Educational Psychology and Infectious Diseases, having authored 7 papers that have together received 123 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (3 papers), Advanced Text Analysis Techniques (3 papers), Topic Modeling (3 papers), Sentiment Analysis and Opinion Mining (2 papers), Natural Language Processing Techniques (2 papers), Text and Document Classification Technologies (2 papers), Speech and dialogue systems (1 paper) and Language, Metaphor, and Cognition (1 paper). The work is most often cited by research in Artificial Intelligence (100 citations), Information Systems (21 citations), Health Informatics (1 citation), Management of Technology and Innovation (3 citations) and Computer Vision and Pattern Recognition (8 citations). Suyang Dai has collaborated with scholars based in China, Australia and Finland. Frequent co-authors include Shanfeng Zhu, Hiroshi Mamitsuka, Ronghui You, Zihan Zhang, Ziye Wang, Xiaodi Huang, Zhiyong Lu, Wei Zhou, Fei Yang and Jun Huang. Their work appears in journals such as IEEE/ACM Transactions on Audio Speech and Language Processing, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Bioinformatics and arXiv (Cornell University).
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.