Big data analytics for the prediction of tourist preferences worldwide

Big Data analytics and machine learning are being adopted in a range of industries - but how can these technologies be utilised and what can they offer to the tourism industry? In the process of their journeys and in their decision-making processes, people who travel contribute to the generation of...

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Bibliographic Details
Main Authors Padmaja, N. (Author), Subramaniam, Rajalakshmi (Author), Mohapatra, Sanjay (Author)
Format Electronic eBook
LanguageEnglish
Published Bingley, U.K. : Emerald Publishing Limited, 2024.
SeriesEmerald points.
Subjects
Big data.
Tourism > Forecasting.
elektronické knihy
electronic books
Online AccessFull text
ISBN9781835493403
DOI10.1108/9781835493380
Physical Description1 online resource (144 pages).

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Table of Contents:
  • Chapter 1. Introduction
  • Chapter 2. Literature Review
  • Chapter 3. Design of the Proposed System
  • Chapter 4. Predicting Preferences of International and Domestic Tourists Using Association Rule Mining Algorithm
  • Chapter 5. Predicting Hotel Preferences of International and Domestic Tourists Using Pointwise Mutual Information
  • Chapter 6. Big Data Analytics in Predicting Tourist Preferences Based on Hotel Ratings Using Multiclass Multilabel Classification Algorithm
  • Chapter 7. Performance Evaluation
  • Chapter 8. Discussion and Conclusion.

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