Clifton Phua
- Artificial Intelligence top 5%
- Information Systems top 5%
- Computer Vision and Pattern Recognition top 5%
- Computer Networks and Communications top 10%
- Electrical and Electronic Engineering
- Co-authors
- Vincent LeeDamminda AlahakoonJit BiswasRoss W. GaylerKate Smith‐MilesPhilip YapJing LinMounir Mokhtari
- Topics
- Context-Aware Activity Recognition Systems (8 papers)Anomaly Detection Techniques and Applications (7 papers)Imbalanced Data Classification Techniques (4 papers)
- Journals
- European Journal of Operational ResearchIEEE Transactions on Knowledge and Data EngineeringJournal of Machine Learning Research
- Partner nations
- SingaporeAustraliaUnited States
In The Last Decade
Clifton Phua
18 papers receiving 577 citations
Peers
Comparison fields: 5 of 78
- Artificial Intelligence 419
- Information Systems 163
- Computer Vision and Pattern Recognition 150
- Computer Networks and Communications 107
- Electrical and Electronic Engineering 89
Countries citing papers authored by Clifton Phua
This map shows the geographic impact of Clifton Phua'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 Clifton Phua with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Clifton Phua more than expected).
Fields of papers citing papers by Clifton Phua
This network shows the impact of papers produced by Clifton Phua. 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 Clifton Phua. The network helps show where Clifton Phua may publish in the future.
Co-authorship network of co-authors of Clifton Phua
This figure shows the co-authorship network connecting the top 25 collaborators of Clifton Phua. A scholar is included among the top collaborators of Clifton Phua based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Clifton Phua. Clifton Phua is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Detecting click fraud in online advertising: a data mining approach | 45 |
| 2 | 75 | |
| 3 | 3 | |
| 4 | 35 | |
| 5 | 5 | |
| 6 | 35 | |
| 7 | 7 | |
| 8 | 10 | |
| 9 | Possibilistic behavior recognition in smart homes for cognitive assistance | 4 |
| 10 | 23 | |
| 11 | 14 | |
| 12 | 11 | |
| 13 | 18 | |
| 14 | 17 | |
| 15 | Adaptive spike detection for resilient data stream mining | 11 |
| 16 | 4 | |
| 17 | 6 | |
| 18 | 323 |
About Clifton Phua
Clifton Phua is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications, having authored 18 papers that have together received 646 indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (8 papers), Anomaly Detection Techniques and Applications (7 papers) and Imbalanced Data Classification Techniques (4 papers). The work is most often cited by research in Artificial Intelligence (419 citations), Computer Vision and Pattern Recognition (150 citations) and Information Systems (163 citations). Clifton Phua has collaborated with scholars based in Singapore, Australia and United States. Frequent co-authors include Vincent Lee, Damminda Alahakoon, Jit Biswas, Ross W. Gayler, Kate Smith‐Miles, Philip Yap, Jing Lin, Mounir Mokhtari, Hamdi Aloulou and Minh Nhut Nguyen. Their work appears in journals such as European Journal of Operational Research, IEEE Transactions on Knowledge and Data Engineering and Journal of Machine Learning Research.
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.