Real-world Conversational AI for Hotel Bookings
Bai Li, Nanyi Jiang, Joey Sham, Henry Shi, Hussein Fazal

TL;DR
This paper describes a real-world conversational AI system for hotel search and booking via text messaging, highlighting its architecture, deployment at scale, and industry-specific challenges and opportunities.
Contribution
It introduces a scalable, deployed chatbot architecture for hotel bookings that integrates machine learning for key NLP tasks in a commercial setting.
Findings
Handles tens of thousands of hotel searches daily
Addresses industry-specific challenges in deploying conversational AI
Demonstrates effective integration of dialogue management and ML models
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.
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Taxonomy
TopicsTopic Modeling · AI in Service Interactions · Speech and dialogue systems
