Sistema de recomendación para nuevos usuarios de Airbnb
Autor:
Pardo-Cuesta, Raquel
Fecha:
23/07/2019Palabra clave:
Tipo de Ítem:
masterThesisResumen:
Las recomendaciones de productos para nuevos usuarios de una compañía, problema
conocido como cold start, supone nuevos métodos de inteligencia artificial para poder llevar a
cabo la recomendación de un producto con cierta proporción de aciertos. El objetivo de este
trabajo es el tratamiento de una base de datos de usuarios de Airbnb con técnicas de machine
learning para lograr un sistema de recomendación. Este sistema de recomendación sugerirá,
entre un número determinado de destinos, la elección más probable en función de la actividad
del usuario con la página web, su edad y género y otros factores. Para ello, se aplicarán varias
técnicas de aprendizaje automático, tanto en entornos Big Data como en los convencionales,
y se utilizarán los de mejores resultados para elaborar el sistema de recomendación.
Descripción:
Product recommendations for new users of a company, problem known as cold start,
suppose new artificial intelligence methods to be able to carry out the recommendation of a
product with a certain proportion of correct answers. The aim of this work is the treatment
of an Airbnb user’s database with machine learning techniques to achieve a recommendation
system. This recommendation system will suggest, among a number of possible destinations,
the most likely choice taking into account the user’s activity into the website, his/her age and
gender and other factors. To do so, several automatic learning techniques are applied, both in
Big Data and conventional environments, and the best predictive results are going to be used
to elaborate the recommendation system.
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