James Mapp
Impact in
- Signal Processing top 2%
- Time Series Analysis and Forecasting
- Music and Audio Processing
- Artificial Intelligence top 5%
- Anomaly Detection Techniques and Applications
- Advanced Text Analysis Techniques
Papers in ⓘ
-
- Fish Ecology and Management Studies 1
-
- Paleontology and Evolutionary Biology 1
- Co-authors
- Jason Lines (1 shared paper)Jon Hills (1 shared paper)Anthony Bagnall (1 shared paper)Ewan Hunter (2 shared papers)Mark Fisher (2 shared papers)Jeroen van der Kooij (1 shared paper)Mark Greco (1 shared paper)G.D. Bell (1 shared paper)
- Journals
- Data Mining and Knowledge Discovery (1 paper)Fisheries Research (1 paper)Journal of Fish Biology (1 paper)eScholarship (California Digital Library) (1 paper)
- Partner nations
- United KingdomAustralia
In The Last Decade
James Mapp
4 papers receiving 376 citations
Hit Papers
Peers
Comparison fields: 5 of 61
- Signal Processing 284
- Artificial Intelligence 215
- Aquatic Science 24
- Economics and Econometrics 81
- Global and Planetary Change 48
Countries citing papers authored by James Mapp
This map shows the geographic impact of James Mapp'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 Mapp with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Mapp more than expected).
Fields of papers citing papers by James Mapp
This network shows the impact of papers produced by James Mapp. 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 Mapp. The network helps show where James Mapp may publish in the future.
Co-authors
The 11 scholars most cited alongside James Mapp, 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 | 330 |
| 2 | 2017 | 44 | |
| 3 | 2016 | 12 | |
| 4 | Energy-efficient purchasing by state and local government: Triggering a landslide down the slippery slope to market transformation | 2004 | 4 |
About James Mapp
James Mapp is a scholar working on Nature and Landscape Conservation, Paleontology, Computer Vision and Pattern Recognition, Radiation and Signal Processing, having authored 4 papers that have together received 390 indexed citations. Recurring topics across this work include Paleontology and Evolutionary Biology (1 paper), Fish Ecology and Management Studies (1 paper), Genetic and phenotypic traits in livestock (1 paper), Advanced X-ray Imaging Techniques (1 paper), Energy, Environment, and Transportation Policies (1 paper), Optical measurement and interference techniques (1 paper), Time Series Analysis and Forecasting (1 paper) and Energy Efficiency and Management (1 paper). The work is most often cited by research in Signal Processing (284 citations), Artificial Intelligence (215 citations), Aquatic Science (24 citations), Economics and Econometrics (81 citations) and Global and Planetary Change (48 citations). James Mapp has collaborated with scholars based in United Kingdom and Australia. Frequent co-authors include Jason Lines, Jon Hills, Anthony Bagnall, Ewan Hunter, Mark Fisher, Jeroen van der Kooij, Mark Greco, G.D. Bell, Robert Atwood and Jeffrey Harris. Their work appears in journals such as Data Mining and Knowledge Discovery, Fisheries Research, Journal of Fish Biology and eScholarship (California Digital Library).
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.