Identifying locations from geospatial trajectories
- Submitting institution
-
The University of Warwick
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 5978
- Type
- D - Journal article
- DOI
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10.1016/j.jcss.2015.10.005
- Title of journal
- Journal of Computer and System Sciences
- Article number
- -
- First page
- 566
- Volume
- 82
- Issue
- 4
- ISSN
- 0022-0000
- Open access status
- Out of scope for open access requirements
- Month of publication
- June
- Year of publication
- 2016
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
I - Artificial Intelligence and Human-Centred Computing
- Citation count
- 12
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper proposed the Gradient-based Visit Extractor (GVE) algorithm for extracting periods of low mobility from geospatial data. GVE was the first method resilient to noise and partial data, addressing drawbacks of existing techniques. The method was subsequently refined in collaboration with Jaguar Land Rover (contact: Dr Alex Mouzakitis, amouzak1@jaguarlandrover.com), and a prototype has been developed for in-vehicle applications (JLR and Van Hinsbergh, GeoAI 2018). The work led to a Royal Society Industry Fellowship for Griffiths (IF140091), and subsequent funding from JLR and EPSRC including TASCC: The Cooperative CAR (£2M, EPSRC EP/N012380/1) and iCASE PhD projects (iCASE 15220095 and 19000092).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -