Visitor Assistant Tools Based on Machine Learning Approaches in Cultural Heritage Contexts

Abstract

Nowadays, pervasive digital technologies, innovative tools, and fruition strategies are generally adopted in the Cultural Heritage (CH) field to improve the quality of services and to enhance visitor experiences. To these aims, expert systems based on learning approaches are specifically designed. In this paper we describe a machine learning approach, implemented in a software tool, that can be usefully used to assist and tov support visitors in cultural spaces. The deployed system architecture is deeply analysed and, finally, a study in CH context is reported.