Knowledge-Assisted Ranking: A Visual Analytic Application for Sport Event Data
- Submitting institution
-
Swansea University / Prifysgol Abertawe
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 22327
- Type
- D - Journal article
- DOI
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10.1109/MCG.2015.25
- Title of journal
- IEEE Computer Graphics and Applications
- Article number
- -
- First page
- 72
- Volume
- 36
- Issue
- -
- ISSN
- 1558-1756
- Open access status
- Out of scope for open access requirements
- Month of publication
- December
- Year of publication
- 2015
- URL
-
http://cs.swan.ac.uk/~csbob/research/
- Supplementary information
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- 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
-
-
- Research group(s)
-
-
- Citation count
- 8
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Summarising long duration video data for subsequent analysis is a significant problem with great applications, including sports performance analysis. In a two-year close collaboration with the Welsh Rugby Union and Sports Scientists we combined mathematical regression techniques with visualization to automatically rank the importance of thousands of sporting events in the first interactive system of its kind. This work was featured in three international keynote talks. It is one underpinning work of a spin out company known as SportsViz.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -