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
- Co-authors
- Jon Hills (1 shared paper)Anthony Bagnall (1 shared paper)Jason Lines (1 shared paper)Mark Fisher (2 shared papers)Ewan Hunter (2 shared papers)Jeroen van der Kooij (1 shared paper)Robert Atwood (1 shared paper)G.D. Bell (1 shared paper)
- Journals
- Data Mining and Knowledge Discovery (1 paper)Journal of Fish Biology (1 paper)Fisheries Research (1 paper)eScholarship (California Digital Library) (1 paper)
- Partner nations
- United KingdomAustralia
In The Last Decade
James Mapp
4 papers receiving 385 citations
James Mapp's Hit Papers
Peers
Comparison fields: 5 of 63
- Signal Processing 286
- Artificial Intelligence 219
- Aquatic Science 24
- Economics and Econometrics 82
- Global and Planetary Change 49
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 | 339 |
| 2 | 2017 | 45 | |
| 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 400 indexed citations. Recurring topics across this work include Fish Ecology and Management Studies (1 paper), Energy Efficiency and Management (1 paper), Optical measurement and interference techniques (1 paper), Sustainable Development and Policies (1 paper), Marine and fisheries research (1 paper), Genetic and phenotypic traits in livestock (1 paper), Time Series Analysis and Forecasting (1 paper) and Music and Audio Processing (1 paper). The work is most often cited by research in Signal Processing (286 citations), Artificial Intelligence (219 citations), Aquatic Science (24 citations), Economics and Econometrics (82 citations) and Global and Planetary Change (49 citations). James Mapp has collaborated with scholars based in United Kingdom and Australia. Frequent co-authors include Jon Hills, Anthony Bagnall, Jason Lines, Mark Fisher, Ewan Hunter, Jeroen van der Kooij, Robert Atwood, G.D. Bell, Mark Greco and Jeffrey Harris. Their work appears in journals such as Data Mining and Knowledge Discovery, Journal of Fish Biology, Fisheries Research 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.