Abstract
ABSTRACTThis article describes a method to provide adapted visit tours in art museums according to the preferences expressed by the visitor and exhibits prestige. It is based on a dual approach with, on the one hand an automatic textual analysis of the official information available online (labels of exhibits) that allows to rank the exhibit attractiveness for a standard museum visitor. On the other hand, individual preferences are also taken into account to adapt the visit according to the personal cultural awareness of the visitor. We use operations research to solve a routing optimization problem, aiming at finding a visit tour with time constraints and maximization of the visitor satisfaction. Depending on the instance size and the problem scale, an integer linear programming (ILP) model and a greedy algorithm are proposed to recommend personalized visit tours and applied on two museums: ‘Musée de l’Orangerie’ in Paris and ‘National Gallery’ in London. The obtained results show that it is possible to recommend a good tour to visitors of an art museum by taking into account the common prestige of the exhibits and the individual interests, joining automatic text summarization and routing optimization in a limited geographical space.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Geographical Information Science
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
