Truth discovery in crowdsourced detection of spatial events
- Submitting institution
-
University of St Andrews
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 252072103
- Type
- D - Journal article
- DOI
-
10.1109/TKDE.2015.2504928
- Title of journal
- IEEE Transactions on Knowledge and Data Engineering
- Article number
- -
- First page
- 1047
- Volume
- 28
- Issue
- 4
- ISSN
- 1041-4347
- Open access status
- Out of scope for open access requirements
- Month of publication
- December
- Year of publication
- 2015
- 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
-
3
- Research group(s)
-
A - Artificial Intelligence
- Citation count
- 23
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This publication is from the project "Collaborative Intelligence Analysis" led by Norman, a collaboration with UCLA and Honeywell, funded jointly by UK-MoD and US-DoD through the NIS-ITA programme (http://nis-ita.org/). The project focussed on developing techniques to support analytics for military intelligence, where detection of located events from open and crowdsourced data is a significant challenge. Reliability of crowdsourced event reports is affected by reliability of participants but also by their mobility. Our model mitigates this combined uncertainty avoiding location tracking. Research from the general project was identified by US and UK governments as a key highlight from the 10-year programme.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
