Bin Wang
- Artificial Intelligence top 0.5%
- Topic Modeling 28
- Privacy-Preserving Technologies in Data 19
- Anomaly Detection Techniques and Applications 19
- Adversarial Robustness in Machine Learning 18
- Natural Language Processing Techniques 14
- Text and Document Classification Technologies 12
- Information Systems top 0.5%
- Web Data Mining and Analysis 12
- Signal Processing top 5%
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- Network Security and Intrusion Detection 13
- Co-authors
- Quan WangLi GuoShu GuoGareth J. F. JonesLihong WangZongcheng JiYang XuJianqin Yin
- Journals
- IEEE Transactions on Dependable and Secure Computing (7 papers)IEEE Access (3 papers)IEEE Transactions on Neural Networks and Learning Systems (3 papers)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Bin Wang
180 papers receiving 2.7k citations
Hit Papers
Peers
Comparison fields: 5 of 144
- Artificial Intelligence 1.7k
- Information Systems 811
- Computer Vision and Pattern Recognition 602
- Computer Science Applications 95
- Signal Processing 188
Countries citing papers authored by Bin Wang
This map shows the geographic impact of Bin Wang'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 Bin Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bin Wang more than expected).
Fields of papers citing papers by Bin Wang
This network shows the impact of papers produced by Bin Wang. 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 Bin Wang. The network helps show where Bin Wang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Bin Wang, 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 | 4 | |
| 2 | 2025 | 3 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 5 | |
| 5 | 2024 | 0 | |
| 6 | 2024 | 0 | |
| 7 | 2024 | 4 | |
| 8 | 2024 | 3 | |
| 9 | 2023 | 4 | |
| 10 | 2023 | 11 | |
| 11 | 2023 | 3 | |
| 12 | 2022 | 7 | |
| 13 | 2022 | 13 | |
| 14 | 2021 | 4 | |
| 15 | 2021 | 4 | |
| 16 | 2020 | 3 | |
| 17 | 2020 | 8 | |
| 18 | Enhancing Keyword Search in Relational Databases Using Nearly Duplicate Records. | 2010 | 3 |
| 19 | Tree-like database design model for expansible application | 2006 | 2 |
| 20 | An Analysis of Question Processing of English and Chinese for the NTCIR 5 Cross-Language Question Answering Task | 2005 | 1 |
About Bin Wang
Bin Wang is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition, having authored 202 papers that have together received 2.9k indexed citations. Recurring topics across this work include Topic Modeling (28 papers), Privacy-Preserving Technologies in Data (19 papers), Anomaly Detection Techniques and Applications (19 papers), Adversarial Robustness in Machine Learning (18 papers), Natural Language Processing Techniques (14 papers), Network Security and Intrusion Detection (13 papers), Text and Document Classification Technologies (12 papers) and Web Data Mining and Analysis (12 papers). The work is most often cited by research in Artificial Intelligence (1.7k citations), Information Systems (811 citations) and Computer Vision and Pattern Recognition (602 citations). Bin Wang has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Quan Wang, Li Guo, Shu Guo, Gareth J. F. Jones, Lihong Wang, Zongcheng Ji, Yang Xu, Jianqin Yin, Wenqing Zheng and Fei Xu. Their work appears in journals such as IEEE Transactions on Dependable and Secure Computing, IEEE Access, IEEE Transactions on Neural Networks and Learning Systems, Neurocomputing and IEEE Internet of Things Journal.
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.