Integrating Ontologies and Fuzzy Logic to Represent User-Trustworthiness in Recommender Systems Porcel Gallego, Carlos Gustavo Martínez Cruz, Carmen Bernabé Moreno, Juan Tejeda Lorente, Álvaro Herrera Viedma, Enrique Recommender system Ontologies User profiles Fuzzy linguistic modelling Trust-network based system Information Technology and Quantitative Management (ITQM 2015) 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. 2020-12-22T10:54:00Z 2020-12-22T10:54:00Z 2015 info:eu-repo/semantics/conferenceObject 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] http://hdl.handle.net/10481/65097 10.1016/j.procs.2015.07.050 eng http://creativecommons.org/licenses/by-nc-nd/3.0/es/ info:eu-repo/semantics/openAccess Atribución-NoComercial-SinDerivadas 3.0 España Elsevier