A Web Platform and a Context Aware Recommender System for Active Sport Events

Abstract

Customer recommendations have proved to boost sales, increase customer satisfaction and improve user experience, making recommender systems an important tool for businesses. While recommendations of items such as products or movies, when browsing online, are heavily examined and several recommendation algorithms and systems are developed, still recommendation systems for events present unique challenges. This becomes even more challenging when recommending active sport events to users, due to inherent restrictions and limitations. This paper presents a context aware recommender system developed and integrated to the ST76 web platform, which enables for the first time, to the best of our knowledge, to provide recommendations of users that are more likely to participate in an upcoming active sport event. Also, we showcase the importance of the ST76 platform and recommender system for sports tourism, through the analysis of the economic impact of an active sport event hosted on the platform.