Designing a recommender system for board games
Michael Antonius Ion, Dimitris Sacharidis, Hannes Werthner · 2020
Interest in board games has grown dramatically in the recent years, and so has the number of releases per year. Consumers can find it hard for themselves to choose the next board game to delve into, and often rely on curated lists and expert recommendations. At the same time, the broad availability of qualitative and quantitative data about board games makes this domain ripe for the application of automated recommendations. In this paper, we employ existing and novel techniques for recommending board games.