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Chatbot for Lisbon Tourism: A Proof of Concept Using LLMs and Retrieval-Augmented Generation to Assist Travelers in Choosing Airbnb Accommodations
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Orientador(es)
Resumo(s)
This work focuses on exploring chatbot technologies, proceed by developing, evaluating and
deploying a prototype solution of a chatbot to help tourists in Lisbon, with the initial focus on
helping tourists choosing an Airbnb to stay in given a set number of properties provided by
our chosen dataset. The two main technologies we will investigate to power our chatbot with
a LLM are finetuning and Retrieval Augmented Generation (RAG) in which we explore their
uses and practical scenarios, but the version we developed will be using RAG with the help of
LangFlow and Vector databases to deploy the chatbot. The chatbot was tested through a
structured user survey, and feedback was collected to evaluate its usability, accuracy, and
overall utility. Results indicate that users appreciated the ability to ask natural language
questions and receive context-aware answers, although limitations in understanding complex
or multi-step prompts were noted. This work contributes to the continuous growth of the AI
and Chatbots world, and studies its potential uses in Tourism, demonstrating a practical case
scenario of the use of RAG to implement a chatbot, while also providing insight into
differences and benefits of using RAG or Fine-tuning in each scenario for LLM deployment in
other works.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence
Palavras-chave
Chatbot Tourism Lisbon Retrieval Augmented Generation LangFlow Finetuning Large Language Models Proof of Concept SDG 8 - Decent work and economic growth SDG 9 - Industry, innovation and infrastructure SDG 11 - Sustainable cities and communities