Jon Hills
Impact in
- Signal Processing top 0.5%
- Time Series Analysis and Forecasting
- Music and Audio Processing
- Artificial Intelligence top 2%
- Anomaly Detection Techniques and Applications
- Advanced Text Analysis Techniques
- Neural Networks and Applications
Papers in
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- Time Series Analysis and Forecasting 5
- Music and Audio Processing 3
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- Complex Systems and Time Series Analysis 3
- Co-authors
- Anthony J. Bagnall (7 shared papers)Jason Lines (5 shared papers)Aaron George Bostrom (2 shared papers)Luke M. Davis (3 shared papers)James Mapp (1 shared paper)Beatriz de la Iglesia (1 shared paper)Graeme Richards (1 shared paper)
- Journals
- Journal of Intelligent Information Systems (1 paper)Data Mining and Knowledge Discovery (1 paper)IEEE Transactions on Knowledge and Data Engineering (1 paper)Lecture notes in computer science (1 paper)UEA Digital Repository (University of East Anglia) (3 papers)
- Partner nations
- United Kingdom
In The Last Decade
Jon Hills
7 papers receiving 1.1k citations
Jon Hills's Hit Papers
Peers
Comparison fields: 5 of 86
- Signal Processing 972
- Artificial Intelligence 798
- Economics and Econometrics 271
- Management Science and Operations Research 63
- Computer Vision and Pattern Recognition 89
Countries citing papers authored by Jon Hills
This map shows the geographic impact of Jon Hills'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 Jon Hills with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jon Hills more than expected).
Fields of papers citing papers by Jon Hills
This network shows the impact of papers produced by Jon Hills. 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 Jon Hills. The network helps show where Jon Hills may publish in the future.
Co-authors
The 7 scholars most cited alongside Jon Hills, 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 | Classification of time series by shapelet transformation Hit paper breakdown → | 2013 | 408 |
| 2 | Time-Series Classification with COTE: The Collective of Transformation-Based Ensembles Hit paper breakdown → | 2015 | 326 |
| 3 | 2012 | 286 | |
| 4 | 2012 | 84 | |
| 5 | 2016 | 49 | |
| 6 | 2013 | 9 | |
| 7 | 2012 | 5 |
About Jon Hills
Jon Hills is a scholar working on Signal Processing, Economics and Econometrics, Computational Theory and Mathematics, Artificial Intelligence and Information Systems, having authored 7 papers that have together received 1.2k indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (5 papers), Complex Systems and Time Series Analysis (3 papers), Music and Audio Processing (3 papers), Rough Sets and Fuzzy Logic (2 papers), Data Mining Algorithms and Applications (2 papers), Fuzzy Logic and Control Systems (1 paper), Anomaly Detection Techniques and Applications (1 paper) and Imbalanced Data Classification Techniques (1 paper). The work is most often cited by research in Signal Processing (972 citations), Artificial Intelligence (798 citations), Economics and Econometrics (271 citations), Management Science and Operations Research (63 citations) and Computer Vision and Pattern Recognition (89 citations). Jon Hills has collaborated with scholars based in United Kingdom. Frequent co-authors include Anthony J. Bagnall, Jason Lines, Aaron George Bostrom, Luke M. Davis, James Mapp, Beatriz de la Iglesia and Graeme Richards. Their work appears in journals such as Journal of Intelligent Information Systems, Data Mining and Knowledge Discovery, IEEE Transactions on Knowledge and Data Engineering, Lecture notes in computer science and UEA Digital Repository (University of East Anglia).
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.