In this work we describe a new Smart Tourism System called SMARTCAL, born during the development of a R&D project for supporting the tourism digitalisation, that includes the release of a pilot in Calabria (a region in the South of Italy). The project is a new initiative to support tourism and hospitality industry with a series of statistical tools for the decision makers, to provide digital and smart services for the tourists that want to build their itineraries with flexibility and to improve the valorisation of a particular territory from the economical and tourist point of view. Indeed, the system is designed by considering Points and Events of Interest (PEOI) and their relationship with the local transport systems, with the hospitality industries and with the policy makers. Two major tools are described in the following: a proactive tourist tour planner algorithm, proposed to generate optimised itineraries based on static and dynamic profiling of the users, and a sentiment analysis module that supports decision makers with a scorecard with a set of key indicators.
De Maio, A., Fersini, E., Messina, V., Santoro, F., Violi, A. (2020). Exploiting social data for tourism management: the SMARTCAL project. QUALITY & QUANTITY [10.1007/s11135-020-01049-8].
Exploiting social data for tourism management: the SMARTCAL project
De Maio A.;Fersini E.;Messina v;
2020
Abstract
In this work we describe a new Smart Tourism System called SMARTCAL, born during the development of a R&D project for supporting the tourism digitalisation, that includes the release of a pilot in Calabria (a region in the South of Italy). The project is a new initiative to support tourism and hospitality industry with a series of statistical tools for the decision makers, to provide digital and smart services for the tourists that want to build their itineraries with flexibility and to improve the valorisation of a particular territory from the economical and tourist point of view. Indeed, the system is designed by considering Points and Events of Interest (PEOI) and their relationship with the local transport systems, with the hospitality industries and with the policy makers. Two major tools are described in the following: a proactive tourist tour planner algorithm, proposed to generate optimised itineraries based on static and dynamic profiling of the users, and a sentiment analysis module that supports decision makers with a scorecard with a set of key indicators.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.