Kevin Chiew
Impact in
- Signal Processing top 10%
- Data Management and Algorithms
- Information Systems top 10%
- Data Mining Algorithms and Applications
- Cloud Computing and Resource Management
Papers in
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- Text and Document Classification Technologies 5
- Advanced Clustering Algorithms Research 3
- Algorithms and Data Compression 3
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- Data Mining Algorithms and Applications 4
- Co-authors
- Qinming He (16 shared papers)Hao Huang (10 shared papers)Feng Qian (2 shared papers)Zhenguang Liu (5 shared papers)Deshi Ye (2 shared papers)Liang‐Wei Zhu (2 shared papers)Jianhai Chen (2 shared papers)Wenzhi Chen (2 shared papers)
In The Last Decade
Kevin Chiew
23 papers receiving 214 citations
Peers
Comparison fields: 5 of 47
- Signal Processing 55
- Information Systems 89
- Artificial Intelligence 93
- Geography, Planning and Development 14
- Computer Networks and Communications 56
Countries citing papers authored by Kevin Chiew
This map shows the geographic impact of Kevin Chiew'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 Kevin Chiew with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin Chiew more than expected).
Fields of papers citing papers by Kevin Chiew
This network shows the impact of papers produced by Kevin Chiew. 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 Kevin Chiew. The network helps show where Kevin Chiew may publish in the future.
Co-authors
The 25 scholars most cited alongside Kevin Chiew, 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 37 | |
| 2 | 2013 | 22 | |
| 3 | 2012 | 19 | |
| 4 | 2012 | 18 | |
| 5 | 2014 | 15 | |
| 6 | 2014 | 15 | |
| 7 | 2010 | 13 | |
| 8 | 2014 | 12 | |
| 9 | 2016 | 10 | |
| 10 | 2015 | 9 | |
| 11 | 2009 | 9 | |
| 12 | 2014 | 9 | |
| 13 | 2017 | 6 | |
| 14 | 2013 | 6 | |
| 15 | 2010 | 5 | |
| 16 | 2016 | 5 | |
| 17 | 2013 | 3 | |
| 18 | 2012 | 2 | |
| 19 | 2009 | 2 | |
| 20 | 2014 | 2 |
About Kevin Chiew
Kevin Chiew is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Signal Processing and Statistical and Nonlinear Physics, having authored 23 papers that have together received 223 indexed citations. Recurring topics across this work include Text and Document Classification Technologies (5 papers), Data Mining Algorithms and Applications (4 papers), Data Management and Algorithms (3 papers), Caching and Content Delivery (3 papers), Complex Network Analysis Techniques (3 papers), Advanced Clustering Algorithms Research (3 papers), Algorithms and Data Compression (3 papers) and Optimization and Search Problems (2 papers). The work is most often cited by research in Signal Processing (55 citations), Information Systems (89 citations), Artificial Intelligence (93 citations), Geography, Planning and Development (14 citations) and Computer Networks and Communications (56 citations). Kevin Chiew has collaborated with scholars based in China, Singapore and Vietnam. Frequent co-authors include Qinming He, Hao Huang, Feng Qian, Zhenguang Liu, Deshi Ye, Liang‐Wei Zhu, Jianhai Chen, Wenzhi Chen, Yunjun Gao and Qian Feng. Their work appears in journals such as Expert Systems with Applications, Journal of Intelligent Information Systems, Knowledge and Information Systems, IEEE Transactions on Intelligent Transportation Systems and International Journal of Communication Systems.
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.