Junhu Wang
Impact in
- Signal Processing top 2%
- Data Management and Algorithms
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- Graph Theory and Algorithms
- Data Visualization and Analytics
Papers in
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- Semantic Web and Ontologies 30
- Topic Modeling 9
- Advanced Graph Neural Networks 8
- Algorithms and Data Compression 7
- Natural Language Processing Techniques 6
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- Advanced Database Systems and Queries 43
- Co-authors
- Mao Lin Huang (8 shared papers)Rodney Topor (5 shared papers)Chengfei Liu (12 shared papers)Jeffrey Xu Yu (12 shared papers)Peter Eades (1 shared paper)Xin Wang (9 shared papers)Md. Saiful Islam (14 shared papers)Jianxin Li (10 shared papers)
In The Last Decade
Junhu Wang
112 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 130
- Signal Processing 315
- Computer Vision and Pattern Recognition 362
- Computer Networks and Communications 371
- Artificial Intelligence 525
- Information Systems 186
Countries citing papers authored by Junhu Wang
This map shows the geographic impact of Junhu 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 Junhu Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junhu Wang more than expected).
Fields of papers citing papers by Junhu Wang
This network shows the impact of papers produced by Junhu 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 Junhu Wang. The network helps show where Junhu Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Junhu 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
Showing the 20 most-cited of 121 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 127 | |
| 2 | 2013 | 100 | |
| 3 | 1998 | 75 | |
| 4 | 2017 | 50 | |
| 5 | 2020 | 43 | |
| 6 | 2016 | 39 | |
| 7 | Removing XML data redundancies using functional and equality-generating dependencies | 2005 | 36 |
| 8 | 2010 | 35 | |
| 9 | 2007 | 33 | |
| 10 | 2019 | 31 | |
| 11 | 2019 | 28 | |
| 12 | 2013 | 23 | |
| 13 | 2021 | 22 | |
| 14 | 2014 | 21 | |
| 15 | 2017 | 19 | |
| 16 | 2019 | 16 | |
| 17 | 2008 | 16 | |
| 18 | 2013 | 15 | |
| 19 | 2014 | 14 | |
| 20 | 2015 | 14 |
About Junhu Wang
Junhu Wang is a scholar working on Artificial Intelligence, Computer Networks and Communications, Signal Processing, Computer Vision and Pattern Recognition and Information Systems, having authored 121 papers that have together received 1.2k indexed citations. Recurring topics across this work include Data Management and Algorithms (47 papers), Advanced Database Systems and Queries (43 papers), Semantic Web and Ontologies (30 papers), Graph Theory and Algorithms (16 papers), Topic Modeling (9 papers), Advanced Graph Neural Networks (8 papers), Algorithms and Data Compression (7 papers) and Natural Language Processing Techniques (6 papers). The work is most often cited by research in Signal Processing (315 citations), Computer Vision and Pattern Recognition (362 citations), Computer Networks and Communications (371 citations), Artificial Intelligence (525 citations) and Information Systems (186 citations). Junhu Wang has collaborated with scholars based in Australia, China and Hong Kong. Frequent co-authors include Mao Lin Huang, Rodney Topor, Chengfei Liu, Jeffrey Xu Yu, Peter Eades, Xin Wang, Md. Saiful Islam, Jianxin Li, Michael J. Maher and Yicheng Ni. Their work appears in journals such as Lecture notes in computer science, Proceedings of the VLDB Endowment, World Wide Web, Information Sciences and Data Science and Engineering.
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.