Feely, CiaraCiaraFeelyCaulfield, BrianBrianCaulfieldLawlor, AonghusAonghusLawlorSmyth, BarryBarrySmyth2023-07-252023-07-252020 Sprin2020-10-03978-3-030-58341-5http://hdl.handle.net/10197/24608The 28th International Conference on Case-Based Reasoning (ICCP 2020), Salamanca, Spain (held online due to coronavirus outbreak), 8-12 June 2020Training for the marathon, especially a first marathon, is always a challenge. Many runners struggle to find the right balance between their workouts and their recovery, often leading to sub-optimal performance on race-day or even injury during training. We describe and evaluate a novel case-based reasoning system to help marathon runners as they train in two ways. First, it uses a case-base of training/workouts and race histories to predict future marathon times for a target runner, throughout their training program, helping runners to calibrate their progress and, ultimately, plan their race-day pacing. Second, the system recommends tailored training plans to runners, adapted for their current goal-time target, and based on the training plans of similar runners who have achieved this time. We evaluate the system using a dataset of more than 21,000 unique runners and 1.5 million training/workout sessions.enThe final publication is available at www.springerlink.com.Recommender systemsCBR for health and exerciseMarathon runningRace-time predictionPlan recommendationConference Publication10.1007/978-3-030-58342-2_52020-08-1812/RC/2289_P218/CRT/6183https://creativecommons.org/licenses/by-nc-nd/3.0/ie/