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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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Bibliographic Details
Main Author: Marchetti, Andrea
Other Authors: Lo Duca, Angelica
Format: eBook
Language:English
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
Subjects:
Geographical Data Modeling Analysis
Obstacle Factors
Topic Extraction
Spatiotemporal Influencing Factors
Influencing Factors
Spatiotemporal Estimation Mapping
Green Hotel Certification
Trend Prediction
Spatiotemporal Evolution
Social Network Analysis
Chinese Regional Tourism
Geodetector
Tourist Attraction Reachability Space Model
Space-time Deduction
Relatedness Between Attractions
Socioeconomic And Environmental Drivers
Online Tourism Reviews
Corporate Social Responsibility
Geographic Detector
Major Tourist Cities
Bayesian Stvc Model
Spatial Distribution
Research & Information: General / Bicssc
Network Connection
Node Centrality
Tourist Attraction Clustering
A-level Scenic Spots
Embedding
Spatiotemporal Nonstationary Regression
Tourism Flow
Tour Route Searching
China
Heterogeneous Information Network
Communities
Green Hotel
Tourism Economic Vulnerability
Attraction Image
Agnes Clustering
Geography / Bicssc
Sports Tourism
Trend Analysis
Cellular Signaling Data
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
Description
Summary: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..
Item Description:Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
Physical Description:1 electronic resource (188 p.)
ISBN:9783036550305
9783036550299
books978-3-0365-5030-5

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