Geo Data Science for Tourism

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 tou...

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Detalles Bibliográficos
Otros Autores:	Marchetti, Andrea (Editor), Lo Duca, Angelica (Otro)
Formato:	Libro electrónico
Idioma:	Inglés
Publicado:	Basel MDPI Books 2022
Materias:	Research & information: general Geography green hotel corporate social responsibility green hotel certification Chinese regional tourism socioeconomic and environmental drivers spatiotemporal influencing factors spatiotemporal estimation mapping Bayesian STVC model spatiotemporal nonstationary regression geographical data modeling analysis sports tourism spatial distribution geographic detector influencing factors China A-level scenic spots spatiotemporal evolution trend analysis Geodetector tourism economic vulnerability obstacle factors trend prediction major tourist cities tourism flow cellular signaling data social network analysis network connection node centrality communities relatedness between attractions online tourism reviews heterogeneous information network embedding attraction image topic extraction AGNES clustering tourist attraction clustering tourist attraction reachability space model space-time deduction tour route searching
Ver en Biblioteca Universitat Ramon Llull:	https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009683481306719