Artificial intelligence and machine ...
Vinod, Ben.

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  • Artificial intelligence and machine learning in the travel industry = simplifying complex decision making /
  • Record Type: Electronic resources : Monograph/item
    Title/Author: Artificial intelligence and machine learning in the travel industry/ edited by Ben Vinod.
    Reminder of title: simplifying complex decision making /
    other author: Vinod, Ben.
    Published: Cham :Springer Nature Switzerland : : 2023.,
    Description: 1 online resource (vi, 182 p.) :ill., digital ;24 cm.
    Notes: 'Previously published in Revenue and Pricing Management Special Issue "Artificial Intelligence and Machine Learning in the Travel Industry" Volume 20, Issue 3, March 2021.'
    [NT 15003449]: 1. Special issue on artificial intelligence/machine learning in travel -- 2. Price elasticity estimation for deep learning-based choice models: an application to air itinerary choices -- 3. An integrated reinforced learning and network competition analysis for calibrating airline itinerary choice models with constrained demand -- 4. Decoupling the individual effects of multiple marketing channels with state space models -- 5. Competitive revenue management models with loyal and fully flexible customers -- 6. Demand estimation from sales transaction data: practical extensions -- 7. How recommender systems can transform airline offer construction and retailing -- 8. A note on the advantage of context in Thompson sampling -- 9. Shelf placement optimization for air products -- 10. Applying reinforcement learning to estimating apartment reference rents -- 11. Machine learning approach to market behavior estimation with applications in revenue management -- 12. Multi-layered market forecast framework for hotel revenue management by continuously learning market dynamics -- 13. Artificial Intelligence in travel -- 14. The key to leveraging AI at scale -- 15. The future of AI is the market.
    Contained By: Springer Nature eBook
    Subject: Tourism - Technological innovations. -
    Online resource: https://doi.org/10.1007/978-3-031-25456-7
    ISBN: 9783031254567
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