James Hammerton
Impact in
- Artificial Intelligence top 5%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
- Text and Document Classification Technologies
- Speech and dialogue systems
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- Data Quality and Management
Papers in
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- Natural Language Processing Techniques 5
- Topic Modeling 5
- Privacy-Preserving Technologies in Data 1
- Text Readability and Simplification 1
- Speech Recognition and Synthesis 1
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- Cloud Data Security Solutions 1
- Web Data Mining and Analysis 1
- Co-authors
- Susan Armstrong (1 shared paper)Walter Daelemans (1 shared paper)Kris Jack (1 shared paper)Michael Granitzer (1 shared paper)Erik Tjong Kim Sang (2 shared papers)Anja Belz (1 shared paper)Stasinos Konstantopoulos (1 shared paper)Nicola Cancedda (1 shared paper)
- Journals
- Applied Physics Letters (1 paper)Connection Science (1 paper)University of Brighton Repository (University of Brighton) (1 paper)Data Archiving and Networked Services (DANS) (1 paper)
- Partner nations
- NetherlandsBelgiumGermany
In The Last Decade
James Hammerton
7 papers receiving 208 citations
Peers
Comparison fields: 5 of 44
- Artificial Intelligence 206
- Management Science and Operations Research 32
- Information Systems 27
- Computer Vision and Pattern Recognition 12
- Signal Processing 6
Countries citing papers authored by James Hammerton
This map shows the geographic impact of James Hammerton'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 James Hammerton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Hammerton more than expected).
Fields of papers citing papers by James Hammerton
This network shows the impact of papers produced by James Hammerton. 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 James Hammerton. The network helps show where James Hammerton may publish in the future.
Co-authors
The 13 scholars most cited alongside James Hammerton, 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 | 2003 | 158 | |
| 2 | 2000 | 42 | |
| 3 | 2001 | 10 | |
| 4 | 1998 | 10 | |
| 5 | 2012 | 8 | |
| 6 | 2001 | 4 | |
| 7 | 2001 | 1 |
About James Hammerton
James Hammerton is a scholar working on Artificial Intelligence, Information Systems, Molecular Biology, Management Science and Operations Research and Electrical and Electronic Engineering, having authored 7 papers that have together received 233 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (5 papers), Topic Modeling (5 papers), Privacy-Preserving Technologies in Data (1 paper), Text Readability and Simplification (1 paper), Speech Recognition and Synthesis (1 paper), Cloud Data Security Solutions (1 paper), Advanced Memory and Neural Computing (1 paper) and Web Data Mining and Analysis (1 paper). The work is most often cited by research in Artificial Intelligence (206 citations), Management Science and Operations Research (32 citations), Information Systems (27 citations), Computer Vision and Pattern Recognition (12 citations) and Signal Processing (6 citations). James Hammerton has collaborated with scholars based in Netherlands, Belgium and Germany. Frequent co-authors include Susan Armstrong, Walter Daelemans, Kris Jack, Michael Granitzer, Erik Tjong Kim Sang, Anja Belz, Stasinos Konstantopoulos, Nicola Cancedda, Miles Osborne and Franck Thollard. Their work appears in journals such as Applied Physics Letters, Connection Science, University of Brighton Repository (University of Brighton) and Data Archiving and Networked Services (DANS).
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.