Semantic reasoning: a path to new possibilities of personalization

Authors:
Yolanda Blanco-Fernández;José J. Pazos-Arias;Alberto Gil-Solla;Manuel Ramos-Cabrer;Martín López-Nores
Affiliations:
Department of Telematics Engineering, University of Vigo, Spain;Department of Telematics Engineering, University of Vigo, Spain;Department of Telematics Engineering, University of Vigo, Spain;Department of Telematics Engineering, University of Vigo, Spain;Department of Telematics Engineering, University of Vigo, Spain
Venue:
ESWC'08 Proceedings of the 5th European semantic web conference on The semantic web: research and applications
Year:
2008

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Abstract

Recommender systems face up to current information overload by selecting automatically items that match the personal preferences of each user. The so-called content-based recommenders suggest items similar to those the user liked in the past, by resorting to syntactic matching mechanisms. The rigid nature of such mechanisms leads to recommend only items that bear a strong resemblance to those the user already knows. In this paper, we propose a novel content-based strategy that diversifies the offered recommendations by employing reasoning mechanisms borrowed from the SemanticWeb. These mechanisms discover extra knowledge about the user's preferences, thus favoring more accurate and flexible personalization processes. Our approach is generic enough to be used in a wide variety of personalization applications and services, in diverse domains and recommender systems. The proposed reasoning-based strategy has been empirically evaluated with a set of real users. The obtained results evidence computational feasibility and significant increases in recommendation accuracy w.r.t. existing approaches where our reasoning capabilities are disregarded.