• DocumentCode
    1572188
  • Title

    Ontology-based classification of unstructured information

  • Author

    Burger, Stefan ; Stieger, Bernd

  • Author_Institution
    Dept. of Comput. Sci., Eastern Michigan Univ., Ypsilanti, MI, USA
  • fYear
    2010
  • Firstpage
    254
  • Lastpage
    259
  • Abstract
    The area of knowledge management (KM) has been addressed with a considerable amount of research in order to develop concepts and technologies for the retrieval of information and knowledge out of a set of heterogeneous data sources. Especially when we deal with files which contain unstructured information, i.e. documents, it is still a huge challenge to classify them automatically into certain domain-dependant categories. Therefore, this paper describes an application and the underlying concepts which are used for a classification based on the available metadata of files, whereas the classification categories can be found in form of ontology classes. This paper discusses experiences and challenges during the implementation with special regard to ontology-based classification algorithms, the underlying framework as well as the importance metadata quality.
  • Keywords
    classification; information retrieval; knowledge management; meta data; ontologies (artificial intelligence); text analysis; document handling; heterogeneous data sources; information retrieval; knowledge management; metadata; ontology-based classification; unstructured information; Business; Data mining; Indexes; Ontologies; Power supplies; Resource description framework; Semantics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Information Management (ICDIM), 2010 Fifth International Conference on
  • Conference_Location
    Thunder Bay, ON
  • Print_ISBN
    978-1-4244-7572-8
  • Type

    conf

  • DOI
    10.1109/ICDIM.2010.5664634
  • Filename
    5664634