AI-Driven Hyperpersonalization in Tourism: A Conversational Agent Using Reinforcement Learning for Dynamic Itinerary Recommendations

Abstract excerpt

<title>Abstract</title> <p>The tourism industry increasingly requires adaptive recommendation systems capable of understanding traveler preferences and learning from user behavior. Traditional conversational agents and retrieval-based systems remain limited by static knowledge and lack continuous personalization. This study presents an integrated framework combining Large Language Models, Retrieval-Augmented Gene...

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• Genomics and Rare Diseases

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Literature Corpus work

e5289be4-bc29-5fe1-bbb5-c7ee0938d51e

DOI

10.21203/rs.3.rs-8658542/v1