Phase-Adaptive Federated Learning for Privacy-Preserving Personalized Travel Itinerary Generation
We propose Phase-Adaptive Federated Learning (PAFL), a novel framework for privacy-preserving personalized travel itinerary generation that dynamically balances privacy and utility through a phase-dependent aggregation mechanism inspired by phase-change materials. (1) PAFL’s primary objective is to...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | Tourism and Hospitality |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-5768/6/2/100 |
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