Reasoning on the semantic web for adaptive hypermedia

Authors:
Lydia Silva-Muñoz;Karina Medina;Marcos Marsicano;Mario Bonjour;José Palazzo M. De Oliveira
Affiliations:
Department of Computer Science, University of Toronto and Instituto de Computación, Universidad de la República, Montevideo, Uruguay;Instituto de Computación, Universidad de la República, Montevideo, Uruguay;Instituto de Computación, Universidad de la República, Montevideo, Uruguay;Instituto de Computación, Universidad de la República, Montevideo, Uruguay;Instituto de Informática, Universidade Federal do Rio Grande do Sul, Rio Grande do Sul, Brasil
Venue:
Journal of Web Engineering
Year:
2008

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Abstract

So far, ontologies have been widely used to convey knowledge across the Semantic Web. Complementing web ontologies with Horn-like rules to assert relations among ontology individuals and properties is part of the ongoing implementation of the Semantic Web. Intelligent Web Adaptive Hypermedia Systems (AHS) are the next generation for adaptive hypermedia on the web. We present a web-based intelligent AHS for e-learning that configures on the fly complex learning objects tailored to the user profile. This automatic configuration is entirely accomplished by reasoning over a hybrid Knowledge Base (KB) composed of ontologies, and Horn-like rules defined on top of ontologies concepts. Interoperability on the semantic level is achieved by using an application profile of standard vocabularies, standard languages for the representation of ontologies and rules, and a standard interface for reasoning functionality.