# name
Aprenentatge automàtic aplicat a la valoració d'allotjaments d'Airbnb

# metadata.dc.description[].value
Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2024, Director: Santi Seguí Mesquida

# metadata.dc.description.abstract[].value
[en] The evaluation of accommodations on the Airbnb platform is a critical factor for both travelers and hosts. In this study, we delve into how machine learning models can predict and contribute to improving the customer
experience. Initially, we propose a solution to address the question “what improvements can be made to an accommodation to increase its rating and what will be the resulting gain?”. The goal is to provide useful informa-
tion to hosts, enabling them to make informed decisions to enhance the quality of their services and, consequently, elevate customer satisfaction and ratings.
This study tackles a fundamental part of this solution: obtaining data, preprocessing, and training predictive models to anticipate accommodation ratings.
Through this research, we explore the possibilities at the intersection of artificial intelligence and the shared accommodation industry. We contribute to the growing field of practical application of machine learning,
laying the groundwork for future improvements and innovations in this domain.

# metadata.dc.rights[].value
memòria: cc-nc-nd (c) Joan Orteu Saiz, 2024

# metadata.dc.source[].value
Treballs Finals de Grau (TFG) - Enginyeria Informàtica

# metadata.dc.title[].value
Aprenentatge automàtic aplicat a la valoració d'allotjaments d'Airbnb