1. Predicting the Personal-Best Times of Speed Skaters Using Case-Based Reasoning
- Author
-
Smyth, Barry, Willemsen, Martijn C., Watson, Ian, Weber, Rosina, Human Technology Interaction, and EAISI Health
- Subjects
Speed skating ,business.industry ,Computer science ,Work (physics) ,Race-time prediction ,030229 sport sciences ,Machine learning ,computer.software_genre ,01 natural sciences ,Variety (cybernetics) ,CBR for health and exercise ,010104 statistics & probability ,03 medical and health sciences ,Race (biology) ,0302 clinical medicine ,Case representation ,Feature (machine learning) ,Case-based reasoning ,Artificial intelligence ,0101 mathematics ,business ,Ice skating ,computer - Abstract
Speed skating is a form of ice skating in which the skaters race each other over a variety of standardised distances. Races take place on specialised ice-rinks and the type of track and ice conditions can have a significant impact on race-times. As race distances increase, pacing also plays an important role. In this paper we seek to extend recent work on the application of case-based reasoning to marathon-time prediction by predicting race-times for speed skaters. In particular, we propose and evaluate a number of case-based reasoning variants based on different case and feature representations to generate track-specific race predictions. We show it is possible to improve upon state-of-the-art prediction accuracy by harnessing richer case representations using shorter races and track-adjusted finish and lap-times.
- Published
- 2020