Information retrieval and recommendation systems

The primary aim of this research line is focused on improving the definition and development of mechanism and models applied to fields such as information access, filtering, retrieval and recommendation systems.

This general objective can be broken down into the following challenges. On the one hand, to study new mechanisms to improve the current approaches on recommender systems, new strategies for user preference prediction, mechanisms for modeling users requirements, as well as new methods for information aggregation. In this sense, we will pay special attention to advanced models that allow the exploitation of information extracted from Internet sources such as social networks, e-Commerce platforms, etc. On the other hand, we propose the study and development of new real-world applications in various fields to test the developed theoretical models, focusing on innovative and useful proposals, to offer effective customized services and improve user experiences.

Contact: Carlos Porcel Gallego

Related Researchers:


  Name Email Area Cat.
Barranco García, Manuel José barranco@ujaen.1aiBHFSScves Computational Intelligence Area PhD
Cobo Martín, Manuel Jesús DaSCI Technology Applications Area PhD
García Cabrera, Lina Guadalupe Computational Intelligence Area PhD
Morente Molinera, Juan Antonio DaSCI Technology Applications Area PhD - Juan de la Cierva
Palomares Carrascosa, Iván ivanpc@ugr.qbqXnQTpNaV@es Data Science and Big Data Area, DaSCI Technology Applications Area PhD
Peis Redondo, Eduardo epeis@ugr.DHxY24tKes Data Science and Big Data Area PhD
Porcel Gallego, Carlos DaSCI Technology Applications Area PhD
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