Graeme Richards
Impact in
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- Artificial Intelligence in Healthcare
- Artificial Intelligence top 10%
- Imbalanced Data Classification Techniques
- Advanced Clustering Algorithms Research
- Metaheuristic Optimization Algorithms Research
Papers in
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- Data Mining Algorithms and Applications 8
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- Imbalanced Data Classification Techniques 2
- Fuzzy Logic and Control Systems 2
- Machine Learning and Data Classification 2
- Advanced Clustering Algorithms Research 1
- Co-authors
- V. J. Rayward‐Smith (5 shared papers)Beatriz de la Iglesia (3 shared papers)Alan Reynolds (1 shared paper)C. Weng (1 shared paper)Peter H. Sönksen (1 shared paper)Wenjia Wang (2 shared papers)Susan Rea (1 shared paper)Jon Hills (1 shared paper)
- Journals
- Journal of Intelligent Information Systems (2 papers)Artificial Intelligence in Medicine (1 paper)European Journal of Operational Research (1 paper)Intelligent Data Analysis (2 papers)Journal of Mathematical Modelling and Algorithms (1 paper)
- Partner nations
- United Kingdom
In The Last Decade
Graeme Richards
10 papers receiving 536 citations
Graeme Richards's Hit Papers
Peers
Comparison fields: 5 of 159
- Health Information Management 49
- Artificial Intelligence 144
- Information Systems 73
- Signal Processing 29
- Computational Theory and Mathematics 35
Countries citing papers authored by Graeme Richards
This map shows the geographic impact of Graeme Richards'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 Graeme Richards with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Graeme Richards more than expected).
Fields of papers citing papers by Graeme Richards
This network shows the impact of papers produced by Graeme Richards. 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 Graeme Richards. The network helps show where Graeme Richards may publish in the future.
Co-authors
The 9 scholars most cited alongside Graeme Richards, 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 | Clustering Rules: A Comparison of Partitioning and Hierarchical Clustering Algorithms Hit paper breakdown → | 2006 | 406 |
| 2 | 2001 | 82 | |
| 3 | 2004 | 29 | |
| 4 | 2005 | 14 | |
| 5 | 2012 | 9 | |
| 6 | 2002 | 8 | |
| 7 | 2013 | 8 | |
| 8 | 2005 | 5 | |
| 9 | A Fast Wrapper Method for Feature Subset Selection. | 2005 | 3 |
| 10 | 2006 | 2 |
About Graeme Richards
Graeme Richards is a scholar working on Information Systems, Artificial Intelligence, Computational Theory and Mathematics, Signal Processing and Health Information Management, having authored 10 papers that have together received 566 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (8 papers), Rough Sets and Fuzzy Logic (4 papers), Imbalanced Data Classification Techniques (2 papers), Artificial Intelligence in Healthcare (2 papers), Fuzzy Logic and Control Systems (2 papers), Machine Learning and Data Classification (2 papers), Data Management and Algorithms (2 papers) and Advanced Clustering Algorithms Research (1 paper). The work is most often cited by research in Health Information Management (49 citations), Artificial Intelligence (144 citations), Information Systems (73 citations), Signal Processing (29 citations) and Computational Theory and Mathematics (35 citations). Graeme Richards has collaborated with scholars based in United Kingdom. Frequent co-authors include V. J. Rayward‐Smith, Beatriz de la Iglesia, Alan Reynolds, C. Weng, Peter H. Sönksen, Wenjia Wang, Susan Rea, Jon Hills and Anthony Bagnall. Their work appears in journals such as Journal of Intelligent Information Systems, Artificial Intelligence in Medicine, European Journal of Operational Research, Intelligent Data Analysis and Journal of Mathematical Modelling and Algorithms.
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.