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Semantic data driven approach for merchandizing optimization

Abstract : The overall objective of this PhD is to explore and propose new approaches leveraging a large volume of heterogeneous data that needs to be integrated and semantically enriched, and recent advances in machine and deep learning techniques, in order to exploit both the increased variety of offers that an airline can make to its customers as well as the knowledge it has of its customers with the ultimate goal of optimizing conversion and purchase. The overall goal of this thesis can be broken down into three main research questions: 1) What piece of content (ancillary services, third-party content) should be recommended and personalized to each traveler? 2) When should a recommendation be made and for which communication channel to optimize conversion? 3) How do we group ancillary services and third-party content and can we learn what often goes together based on purchase logs?
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Submitted on : Wednesday, December 15, 2021 - 5:04:26 PM
Last modification on : Monday, January 3, 2022 - 11:03:46 AM
Long-term archiving on: : Wednesday, March 16, 2022 - 7:33:14 PM


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  • HAL Id : tel-03482149, version 1


Amine Dadoun. Semantic data driven approach for merchandizing optimization. Systems and Control [cs.SY]. Sorbonne Université, 2021. English. ⟨NNT : 2021SORUS191⟩. ⟨tel-03482149⟩



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