Abstract
The use of Linked Data datasets poses new challenges and issues in the development of next-generation systems for recommendation. In this chapter, we present MORE (MOREthan MOvieREcommendation), a Facebook -semantic application that recommends movies to the user by using information coming both from her profile and from semantic datasets. MORE exploits the power of social knowledge bases in the Linked Data cloud (e.g., DBpedia ) to detect semantic affinities among movies by adopting a novel approach that computes similarities based on a semantic vector space model (sVSM). MORE is freely available as a Facebook application and has been evaluated by real users, proving the validity of our approach.
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This feature is currently not implemented in the online version of the application, and is part of our future work.
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Mirizzi, R., Di Noia, T., Di Sciascio, E., Ragone, A. (2012). A Recommender System for Linked Data. In: De Virgilio, R., Guerra, F., Velegrakis, Y. (eds) Semantic Search over the Web. Data-Centric Systems and Applications. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25008-8_12
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