Predicting the Personal-Best Times of Speed Skaters Using Case-Based Reasoning

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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.

Original languageEnglish
Title of host publicationCase-Based Reasoning Research and Development - 28th International Conference, ICCBR 2020, Proceedings
EditorsIan Watson, Rosina Weber
PublisherSpringer
Pages112-126
Number of pages15
ISBN (Print)9783030583415
DOIs
Publication statusPublished - Oct 2020
Event28th International Conference on Case-Based Reasoning, ICCBR 2020 - Salamanca, Spain
Duration: 8 Jun 202012 Jun 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12311 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference28th International Conference on Case-Based Reasoning, ICCBR 2020
CountrySpain
CitySalamanca
Period8/06/2012/06/20

Keywords

  • Case representation
  • CBR for health and exercise
  • Race-time prediction
  • Speed skating

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