Towards a Novel User Satisfaction Modelling for Museum Visit Recommender Systems

Abstract

Modern recommender systems technology appeared in Cultural Heritage application relatively recently, particularly during the dawn of the 21st century. There is already a significant amount of relevant works in the bibliography, which has been primarily empowered by large-scale research and development projects. Various approaches have been adopted from the recommender systems technology, including collaborative filtering, content-based, knowledge-based and hybrid systems. In most of these approaches that focused on museum guidance, which is the focus of this paper, the museum has been assumed to be a form of a gallery and the visitor was treated primarily as a user in seek on engagement and enjoyment. The free museum roaming was the main form of visit that has been considered and targeted, while the educational factors and storytelling aspects have been markedly overlooked. In this paper a new framework for the user satisfaction modelling is being presented that quantifies user satisfaction based on a weighted combination of various probabilistic factors that are being estimated during a museum visit. The goal is to provide a model of user satisfaction that can be used for museum recommenders that could guide either free-roaming visits or guided-tour scenarios for visitors of various motivations and backgrounds.