Personalización de contenidos Web del dominio de e- gobierno mediante ontologías

The World Wide Web has become an everyday tool in our society, comparable to other major media such as radio, television or telephone, its application has been extended to various fields such as education, government and e-commerce where currently the information overload makes it difficult to navigate and use them, is because of this that users should explore areas too dense, making the selection of information they are interested in a tedious task. A mechanism to meet this task are recommendation systems which automatically select and customize the content that best suit the preferences and needs of each user. In the literature have proposed differentpersonalization strategies that researchers have widely adopted in their work.In recent years there has been a promising line of research under the name of the Semantic Web. This initiative aims to describe Web resources with machine-processable metadata, so that they can reason about the semantics and infer relationships among them, that is, discovering new knowledge from already known. Semantic reasoning processes require that data collections being accessed by machines are defined and structured in an appropriate manner such as ontologies, which are consensual and reusable formalization which identifies the concepts and relationships ina domain of application. In this research we present a system for customizing Web content that uses a semantic reasoning mechanism through inference rules associated with a type of user, extracting attributes of ontology of profiles, to relate the concepts in domain ontology, so they get a recommendation of content of interest.