Wang-Cheng Kang
Impact in
- Information Systems top 0.5%
- Recommender Systems and Techniques
-
- Image Retrieval and Classification Techniques
- Advanced Image and Video Retrieval Techniques
- Video Surveillance and Tracking Methods
Papers in
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- Recommender Systems and Techniques 7
-
- Generative Adversarial Networks and Image Synthesis 3
- Visual Attention and Saliency Detection 2
- Image Retrieval and Classification Techniques 2
- Advanced Image and Video Retrieval Techniques 2
- Co-authors
- Julian McAuley (7 shared papers)Wu-Jun Li (1 shared paper)Zhi‐Hua Zhou (1 shared paper)Fang Chen (1 shared paper)Zhaowen Wang (1 shared paper)Charles Rosenberg (1 shared paper)Eric Kim (1 shared paper)Ruining He (1 shared paper)
- Journals
- Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
- Partner nations
- United StatesTaiwanChina
In The Last Decade
Wang-Cheng Kang
12 papers receiving 1.9k citations
Wang-Cheng Kang's Hit Papers
Peers
Comparison fields: 5 of 69
- Information Systems 1.4k
- Computer Vision and Pattern Recognition 730
- Artificial Intelligence 1.1k
- Management Science and Operations Research 383
- Transportation 127
Countries citing papers authored by Wang-Cheng Kang
This map shows the geographic impact of Wang-Cheng Kang'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 Wang-Cheng Kang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wang-Cheng Kang more than expected).
Fields of papers citing papers by Wang-Cheng Kang
This network shows the impact of papers produced by Wang-Cheng Kang. 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 Wang-Cheng Kang. The network helps show where Wang-Cheng Kang may publish in the future.
Co-authors
The 23 scholars most cited alongside Wang-Cheng Kang, 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 | Self-Attentive Sequential Recommendation Hit paper breakdown → | 2018 | 1380 |
| 2 | 2016 | 222 | |
| 3 | 2017 | 145 | |
| 4 | 2019 | 48 | |
| 5 | 2019 | 33 | |
| 6 | 2021 | 32 | |
| 7 | 2018 | 30 | |
| 8 | 2018 | 25 | |
| 9 | 2020 | 21 | |
| 10 | 2016 | 8 | |
| 11 | 2023 | 1 | |
| 12 | 2024 | 1 | |
| 13 | 2024 | 0 |
About Wang-Cheng Kang
Wang-Cheng Kang is a scholar working on Information Systems, Computer Vision and Pattern Recognition, Artificial Intelligence, Management Science and Operations Research and Cognitive Neuroscience, having authored 13 papers that have together received 1.9k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (7 papers), Advanced Graph Neural Networks (4 papers), Generative Adversarial Networks and Image Synthesis (3 papers), Topic Modeling (3 papers), Visual Attention and Saliency Detection (2 papers), Image Retrieval and Classification Techniques (2 papers), Advanced Image and Video Retrieval Techniques (2 papers) and Data Stream Mining Techniques (1 paper). The work is most often cited by research in Information Systems (1.4k citations), Computer Vision and Pattern Recognition (730 citations), Artificial Intelligence (1.1k citations), Management Science and Operations Research (383 citations) and Transportation (127 citations). Wang-Cheng Kang has collaborated with scholars based in United States, Taiwan and China. Frequent co-authors include Julian McAuley, Wu-Jun Li, Zhi‐Hua Zhou, Fang Chen, Zhaowen Wang, Charles Rosenberg, Eric Kim, Ruining He, Jure Leskovec and Derek Zhiyuan Cheng. Their work appears in journals such as Proceedings of the AAAI Conference on Artificial Intelligence.
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.