John D. Holt
Impact in
- Information Systems top 5%
- Data Mining Algorithms and Applications
- Web Data Mining and Analysis
- Artificial Intelligence top 5%
- Text and Document Classification Technologies
- Advanced Text Analysis Techniques
- Advanced Clustering Algorithms Research
- Algorithms and Data Compression
Papers in
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- Data Mining Algorithms and Applications 6
-
- Algorithms and Data Compression 3
- Natural Language Processing Techniques 2
- Imbalanced Data Classification Techniques 1
- Topic Modeling 1
- Co-authors
- Soon M. Chung (6 shared papers)Yanjun Li (2 shared papers)David J. Miller (2 shared papers)Dale F. Cooper (1 shared paper)Jonathan H. Klein (1 shared paper)
- Journals
- European Journal of Operational Research (2 papers)Knowledge and Information Systems (1 paper)Data & Knowledge Engineering (1 paper)The Journal of Supercomputing (1 paper)Bulletin of the American Society for Information Science and Technology (1 paper)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
John D. Holt
9 papers receiving 239 citations
Peers
Comparison fields: 5 of 34
- Information Systems 195
- Artificial Intelligence 207
- Signal Processing 51
- Computational Theory and Mathematics 70
- Computer Vision and Pattern Recognition 19
Countries citing papers authored by John D. Holt
This map shows the geographic impact of John D. Holt'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 John D. Holt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John D. Holt more than expected).
Fields of papers citing papers by John D. Holt
This network shows the impact of papers produced by John D. Holt. 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 John D. Holt. The network helps show where John D. Holt may publish in the future.
Co-authors
The 5 scholars most cited alongside John D. Holt, 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 | 2007 | 169 | |
| 2 | 2001 | 33 | |
| 3 | 2002 | 29 | |
| 4 | 1999 | 22 | |
| 5 | 2007 | 8 | |
| 6 | 1995 | 3 | |
| 7 | 2007 | 3 | |
| 8 | 1988 | 3 | |
| 9 | 1986 | 1 | |
| 10 | 2009 | 0 |
About John D. Holt
John D. Holt is a scholar working on Information Systems, Artificial Intelligence, Computational Theory and Mathematics, Management Science and Operations Research and Control and Systems Engineering, having authored 10 papers that have together received 271 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (6 papers), Rough Sets and Fuzzy Logic (3 papers), Algorithms and Data Compression (3 papers), Complex Systems and Decision Making (2 papers), Natural Language Processing Techniques (2 papers), Data Management and Algorithms (1 paper), Imbalanced Data Classification Techniques (1 paper) and Topic Modeling (1 paper). The work is most often cited by research in Information Systems (195 citations), Artificial Intelligence (207 citations), Signal Processing (51 citations), Computational Theory and Mathematics (70 citations) and Computer Vision and Pattern Recognition (19 citations). John D. Holt has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Soon M. Chung, Yanjun Li, David J. Miller, Dale F. Cooper and Jonathan H. Klein. Their work appears in journals such as European Journal of Operational Research, Knowledge and Information Systems, Data & Knowledge Engineering, The Journal of Supercomputing and Bulletin of the American Society for Information Science and Technology.
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.