کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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393252 | 665586 | 2015 | 17 صفحه PDF | دانلود رایگان |
Recommender systems evaluate and filter the vast amount of information available on the Web, so they can be used to assist users in the process of accessing to relevant information. In the literature we can find countless approaches for generating personalized recommendations and all of them make use of different users’ and/or items’ features. In this sense, building accurate profiles plays an essential role in this context making the system’s success depend to a large extent on the ability of the learned profiles to represent the user’s preferences and needs. An ontology works very well to characterize the users profiles involved in the process of generating recommendations. In this paper we develop an ontology to characterize the trust between users using the fuzzy linguistic modeling, so that 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.
Journal: Information Sciences - Volume 311, 1 August 2015, Pages 102–118