Real-world Conversational AI for Hotel Bookings

Li, Bai, Jiang, Nanyi, Sham, Joey, Shi, Henry, Fazal, Hussein

arXiv.org Machine Learning 

Hussein Fazal SnapTravel Toronto, Canada hussein@snaptravel.com Abstract --In this paper, we present a real-world conversational AI system to search for and book hotels through text messaging. Our architecture consists of a frame-based dialogue management system, which calls machine learning models for intent classification, named entity recognition, and information retrieval subtasks. Our chatbot has been deployed on a commercial scale, handling tens of thousands of hotel searches every day. We describe the various opportunities and challenges of developing a chatbot in the travel industry. Index T erms--conversational AI, task-oriented chatbot, named entity recognition, information retrieval I. I NTRODUCTION Task-oriented chatbots have recently been applied to many areas in e-commerce.

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