• DocumentCode
    2871493
  • Title

    Semantic Linking of a Learning Object Repository to DBpedia

  • Author

    Lama, Manuel ; Vidal, Juan C. ; Otero-Garcia, Estefania ; Bugarín, Alberto ; Barro, Senén

  • Author_Institution
    Centro de Investig. en Tecnoloxias da Informacion (CITIUS), Univ. de Santiago de Compostela, Santiago de Compostela, Spain
  • fYear
    2011
  • fDate
    6-8 July 2011
  • Firstpage
    460
  • Lastpage
    464
  • Abstract
    Learning objects have arisen in response to the need of high-quality and reusable instructional materials. The repositories that hold learning objects allow educators to create and share their instructional contents in an organized infrastructure and where information should be easily searchable. Therefore, a key point of these repositories is the way learning objects are categorized. In this paper, we present an approach for classifying semantically learning objects whose metadata are described in Dublin Core. Specifically, our objective is to annotate automatically the subject of the learning object with instances of the DBpedia ontology, that is, to annotate the learning objects repository with linked open data. The syntactic and semantic analysis of the learning object will drive the selection of the most appropriate categories in the linked data repository.
  • Keywords
    educational courses; educational technology; meta data; ontologies (artificial intelligence); DBpedia ontology; Dublin Core; high-quality instructional materials; instructional contents; learning object repository; metadata; reusable instructional materials; semantic analysis; semantic linking; syntactic analysis; Conferences; Libraries; Measurement; Natural language processing; Ontologies; Resource description framework; Semantics; DBpedia; learning objects; linked data; ontologies;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Learning Technologies (ICALT), 2011 11th IEEE International Conference on
  • Conference_Location
    Athens, GA
  • ISSN
    2161-3761
  • Print_ISBN
    978-1-61284-209-7
  • Electronic_ISBN
    2161-3761
  • Type

    conf

  • DOI
    10.1109/ICALT.2011.143
  • Filename
    5992370