Xiaoxue Zang
- Artificial Intelligence top 10%
- Topic Modeling 9
- Advanced Graph Neural Networks 4
- Speech and dialogue systems 2
- Information Systems top 10%
- Recommender Systems and Techniques 10
- Web Data Mining and Analysis 3
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- Multimodal Machine Learning Applications 5
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- Advanced Bandit Algorithms Research 5
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- Evolutionary Psychology and Human Behavior 3
- Co-authors
- Abhinav RastogiJindong ChenYang SongJun XuXiao ZhangLijuan LiuRuby LeeZecheng He
- Journals
- ACM Transactions on Information Systems (1 paper)arXiv (Cornell University) (2 papers)Proceedings of the AAAI Conference on Artificial Intelligence (2 papers)
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Xiaoxue Zang
19 papers receiving 214 citations
Peers
Comparison fields: 5 of 36
- Artificial Intelligence 152
- Information Systems 67
- Computer Vision and Pattern Recognition 54
- Human-Computer Interaction 12
- Human Factors and Ergonomics 4
Countries citing papers authored by Xiaoxue Zang
This map shows the geographic impact of Xiaoxue Zang'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 Xiaoxue Zang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoxue Zang more than expected).
Fields of papers citing papers by Xiaoxue Zang
This network shows the impact of papers produced by Xiaoxue Zang. 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 Xiaoxue Zang. The network helps show where Xiaoxue Zang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Xiaoxue Zang, 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 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 1 | |
| 4 | 2024 | 5 | |
| 5 | 2024 | 4 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 4 | |
| 8 | 2024 | 0 | |
| 9 | 2024 | 0 | |
| 10 | 2023 | 15 | |
| 11 | 2023 | 6 | |
| 12 | 2023 | 11 | |
| 13 | 2023 | 7 | |
| 14 | 2021 | 5 | |
| 15 | 2021 | 12 | |
| 16 | 2021 | 12 | |
| 17 | 2020 | 101 | |
| 18 | 2017 | 3 | |
| 19 | 2017 | 6 | |
| 20 | 2017 | 2 |
About Xiaoxue Zang
Xiaoxue Zang is a scholar working on Information Systems, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 23 papers that have together received 223 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (10 papers), Topic Modeling (9 papers), Multimodal Machine Learning Applications (5 papers), Advanced Bandit Algorithms Research (5 papers), Advanced Graph Neural Networks (4 papers), Web Data Mining and Analysis (3 papers), Evolutionary Psychology and Human Behavior (3 papers) and Speech and dialogue systems (2 papers). The work is most often cited by research in Artificial Intelligence (152 citations), Information Systems (67 citations) and Computer Vision and Pattern Recognition (54 citations). Xiaoxue Zang has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Abhinav Rastogi, Jindong Chen, Jindong Chen, Yang Song, Jun Xu, Xiao Zhang, Lijuan Liu, Ruby Lee, Zecheng He and Ying Xu. Their work appears in journals such as ACM Transactions on Information Systems, arXiv (Cornell University) and 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.