Content-Based Recommendations for Crags and Climbing Routes

Author:

Ivanova Iustina,Andrić Marina,Ricci Francesco

Abstract

AbstractClimbing is a popular sport for active tourists and recreational sportsmen. Alpine climbing areas, such as the Alps, can attract tourists from all over the world. Various websites, mobile applications, and books are used by climbers to obtain information on important aspects of the available climbing routes, including their properties, location, and especially their difficulty. Considering this large amount of information and options, it is in reality difficult for climbers to properly select which routes to climb. Hence, we propose recommendation technologies aimed at supporting climbers in this decision task. The developed system prototype constructs a climber’s profile with preferences derived from climber’s logbook data collected by a mobile app. Then, the system can recommend suitable crags and climbing routes within the selected crags. The designed interface and the basic computational models for such a system prototype are presented. The proposed technology aims at complementing existing electronic climbing guidebooks and providing decision support to climbers.

Funder

International Federation of IT and Travel Tourism

Publisher

Springer International Publishing

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1. Research on the Fairness of Cold-start Recommender System Based on Federated Learning Framework;Proceedings of the 2023 5th International Conference on Internet of Things, Automation and Artificial Intelligence;2023-11-24

2. Climbing crags recommender system in Arco, Italy: a comparative study;Frontiers in Big Data;2023-10-11

3. Climbing crags repetitive choices and recommendations;Proceedings of the 17th ACM Conference on Recommender Systems;2023-09-14

4. Recommender Systems for Outdoor Adventure Tourism Sports: Hiking, Running and Climbing;Human-Centric Intelligent Systems;2023-07-18

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