Recommender Systems for Outdoor Adventure Tourism Sports: Hiking, Running and Climbing

Abstract

Adventure tourism is a popular and growing segment within the tourism industry that involves, but is not limited to, hiking, running, and climbing activities. These activities attract investment from foreign travelers interested in practicing sports while exploring other countries. As a result, many software companies started developing Artificial Intelligence solutions to enhance tourists’ outdoor adventure experience. One of the leading technologies in this field is recommender systems, which provide personalized recommendations to tourists based on their preferences. While this topic is actively being researched in some sports (running and hiking), other adventure sports disciplines have yet to be fully explored. To standardize the development of intelligence-based recommender systems, we conducted a systematic literature review on more than a thousand scientific papers published in decision support system applications in three outdoor adventure sports, such as running, hiking, and sport climbing. Hence, the main focus of this work is, firstly, to summarize the state-of-the-art methods and techniques being researched and developed by scientists in recommender systems in adventure tourism, secondly, to provide a unified methodology for software solutions designed in this domain, and thirdly, to give further insights into open possibilities in this topic. This literature survey serves as a unified framework for the future development of technologies in adventure tourism. Moreover, this paper seeks to guide the development of more effective and personalized recommendation systems.

Sports Recommender Systems: Overview and Research Issues

“…Such scenarios have to deal with the specific challenge of abrupt changes in weather conditions -in this context, user-specific trust measures have been integrated (e.g., in terms of other users trustworthiness evaluations) with the goal to increase the credibility of recommendations. Ivanova et al [62][63][64]82] introduce different CBF recommendation scenarios in the context of outdoor activities such as hiking, running, and climbing. Specifically, the authors focus on the recommendation of climbing cracks and different routes taking into account a user context specified, for example, in terms of time of the year or persons who participate (e.g., family vs. a team of professional climbers).…”