A framework for collaborative filtering recommender systems


Autoria(s): Ortega Requena, Fernando; Bobadilla Sancho, Jesus; Hernando Esteban, Antonio; Bernal, Jesús
Data(s)

2011

Resumo

As the use of recommender systems becomes more consolidated on the Net, an increasing need arises to develop some kind of evaluation framework for collaborative filtering measures and methods which is capable of not only testing the prediction and recommendation results, but also of other purposes which until now were considered secondary, such as novelty in the recommendations and the users? trust in these. This paper provides: (a) measures to evaluate the novelty of the users? recommendations and trust in their neighborhoods, (b) equations that formalize and unify the collaborative filtering process and its evaluation, (c) a framework based on the above-mentioned elements that enables the evaluation of the quality results of any collaborative filtering applied to the desired recommender systems, using four graphs: quality of the predictions, the recommendations, the novelty and the trust.

Formato

application/pdf

Identificador

http://oa.upm.es/15281/

Idioma(s)

eng

Publicador

E.U. de Informática (UPM)

Relação

http://oa.upm.es/15281/1/INVE_MEM_2011_123405MARIA.pdf

http://www.elsevier.com/locate/eswa

info:eu-repo/semantics/altIdentifier/doi/10.1016/j.eswa.2011.05.021

Direitos

http://creativecommons.org/licenses/by-nc-nd/3.0/es/

info:eu-repo/semantics/openAccess

Fonte

Expert Systems With Applications, ISSN 0957-4174, 2011, Vol. 38

Palavras-Chave #Informática
Tipo

info:eu-repo/semantics/article

Artículo

PeerReviewed