• LYDIA SILVA-MU˜NOZ Instituto de Computaci´on, Universidad de la Rep´ublica Montevideo, Uruguay
  • KARINA MEDINA Instituto de Computaci´on, Universidad de la Rep´ublica Montevideo, Uruguay
  • MARCOS MARSICANO Instituto de Computaci´on, Universidad de la Rep´ublica Montevideo, Uruguay
  • MARIO BONJOUR Instituto de Computaci´on, Universidad de la Rep´ublica Montevideo, Uruguay
  • JOS´E PALAZZO M. de OLIVEIRA Instituto de Inform´atica - Universidade Federal do Rio Grande do Sul Rio Grande do Sul, Brasil


Semantic Web, Adaptive Systems, Reasoning, Ontologies, Standard Metadata, OWL, SWRL


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.



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