Abstract

UTRERA SUST, Eric Bárbaro  and  SIMON CUEVAS, Alfredo Javier. Semantic recommendation systems : A State-of-the-Art Survey. Rev cuba cienc informat [online]. 2017, vol.11, n.2, pp.189-206. ISSN 2227-1899.

ABSTRACT The recommendation systems arise in response to the need to have a content customization tool, using historical information of the user to recommend elements that please him. One of the types of recommendation systems that are having broad coverage in the scientific literature in recent years are semantic recommendation systems. Deficiencies in traditional recommendation systems are solved using variants proposed by semantic recommendation systems. Deficiencies in traditional referral systems are resolved using variants proposed by these systems. This article provides an overview of semantic recommendation systems taking into account their classification, semantic web technologies that use performance, architectures, domains to which they are focused, evaluation criteria and the advantages and disadvantages that they show.

Keywords : information; semantic recommendation systems; semantic web.

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