Semantic Reasoning: A Path to New Possibilities of Personalization

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 Semantic Web. 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...

• Type: Conference
• Year: 2008
• Where: ESWS
• Authors: Yolanda Blanco-Fernández, José J. Pazos Arias, Alberto Gil-Solla, Manuel Ramos Cabrer, Martín López Nores
• Keywords: ESWS 2008, Internet Technology, Recommender Systems, So-called Content-based Recommenders, Syntactic Matching Mechanisms