Sistemas de recomendación y explicaciones basados en grafos de interacción

  1. Marta Caro Martínez
Supervised by:
  1. Juan Antonio Recio García Director
  2. Guillermo Jiménez Díaz Director

Defence university: Universidad Complutense de Madrid

Year of defence: 2022

  1. Raquel Hervás Ballesteros Chair
  2. Javier Arroyo Gallardo Secretary
  3. María del Carmen Romero Ternero Committee member
  4. Albert Fornells Herrera Committee member
  5. Almudena Ruiz Iniesta Committee member
  1. Ingeniería del Software e Inteligencia Artificial

Type: Thesis


Nowadays, with new technologies in all areas of our lives, Internet consumption has advanced quickly. Users can find an infinite number of products to consume in any field, especially through e-commerce, social networks and streaming entertainment. Determining which products are the most suitable according to their needs and preferencies can become a complicated tasd due to the breadth of product offerings that can be found on these platforms. Recommendation systems emerge to solve this problem, facilitating the search and decision-making process. However, when users do not trust the system, recommender systems are not as useful as one might expect because they do not understand how the sustems has concluded that a particular product in suitable for them...