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Geo Data Science for Tourism



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Autore: Marchetti Andrea Visualizza persona
Titolo: Geo Data Science for Tourism Visualizza cluster
Pubblicazione: Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Descrizione fisica: 1 online resource (188 p.)
Soggetto topico: Geography
Research & information: general
Soggetto non controllato: A-level scenic spots
AGNES clustering
attraction image
Bayesian STVC model
cellular signaling data
China
Chinese regional tourism
communities
corporate social responsibility
embedding
Geodetector
geographic detector
geographical data modeling analysis
green hotel
green hotel certification
heterogeneous information network
influencing factors
major tourist cities
network connection
node centrality
obstacle factors
online tourism reviews
relatedness between attractions
social network analysis
socioeconomic and environmental drivers
space-time deduction
spatial distribution
spatiotemporal estimation mapping
spatiotemporal evolution
spatiotemporal influencing factors
spatiotemporal nonstationary regression
sports tourism
topic extraction
tour route searching
tourism economic vulnerability
tourism flow
tourist attraction clustering
tourist attraction reachability space model
trend analysis
trend prediction
Persona (resp. second.): Lo DucaAngelica
MarchettiAndrea
Sommario/riassunto: This reprint describes the recent challenges in tourism seen from the point of view of data science. Thanks to the use of the most popular Data Science concepts, you can easily recognise trends and patterns in tourism, detect the impact of tourism on the environment, and predict future trends in tourism. This reprint starts by describing how to analyse data related to the past, then it moves on to detecting behaviours in the present, and, finally, it describes some techniques to predict future trends. By the end of the reprint, you will be able to use data science to help tourism businesses make better use of data and improve their decision making and operations..
Titolo autorizzato: Geo Data Science for Tourism  Visualizza cluster
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910595079203321
Lo trovi qui: Univ. Federico II
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