The aim of this research is to propose and discuss how a data-driven approach (Cuomo et al., 2020) may improve and enhance the tourist experience in integrated door-to-door mobility services (Schulz et al., 2020). In particular, the data driven approach, thanks to the design of a recommendation system based on a big data analytics engine, makes it possible to: i)rank the tourist preferences for the most attractive Italian destinations in Google; ii)rank the main attractions (leisure, entertainment, culture, etc.) associated with single tourist destinations, obtained from the analysis of relevant thematic websites such as: Tripadvisor, Minube and Travel365.

Enhancing Tourist Experience in Integrated Door-To-Door Mobility Services on Big Social Data Analytics

Giuseppe Festa;
2021-01-01

Abstract

The aim of this research is to propose and discuss how a data-driven approach (Cuomo et al., 2020) may improve and enhance the tourist experience in integrated door-to-door mobility services (Schulz et al., 2020). In particular, the data driven approach, thanks to the design of a recommendation system based on a big data analytics engine, makes it possible to: i)rank the tourist preferences for the most attractive Italian destinations in Google; ii)rank the main attractions (leisure, entertainment, culture, etc.) associated with single tourist destinations, obtained from the analysis of relevant thematic websites such as: Tripadvisor, Minube and Travel365.
2021
978-84-09-30178-2
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11575/137092
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