Integrating Ontologies and Fuzzy Logic to Represent User-Trustworthiness in Recommender Systems
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AuthorPorcel Gallego, Carlos Gustavo; Martínez Cruz, Carmen; Bernabé Moreno, Juan; Tejeda Lorente, Álvaro; Herrera Viedma, Enrique
Recommender systemOntologiesUser profilesFuzzy linguistic modellingTrust-network based system
Porcel, C., Martinez-Cruz, C., Bernabé-Moreno, J., Tejeda-Lorente, Á., & Herrera-Viedma, E. (2015). Integrating ontologies and fuzzy logic to represent user-trustworthiness in recommender systems. Procedia Computer Science, 55, 603-612. [https://doi.org/10.1016/j.procs.2015.07.050]
SponsorshipProjects UJA2013/08/41; TIN2013-40658-P; TIC5299; TIC-5991; TIN2012-36951 co-financed by FEDER and TIC6109
Recommender systems can be used to assist users in the process of accessing to relevant information. In the literature we can find sundry approaches for generating personalized recommendations and all of them make use of different users’ and/or items’ features. Building accurate profiles plays an essential role in this context, so that the system's success depend to a large extent on the ability of the learned profiles to represent the user's preferences. An ontology works very well to characterize the users profiles. In this paper we develop an ontology to characterize the trust between users using the fuzzy linguistic modelling, this way in the recommendation generation process we do not take into account users with similar ratings history but users in which each user can trust. We present our ontology and provide a method to aggregate the trust information captured in the trust-ontology and to update the user profiles based on the feedback.