• Title of article

    Providing metrics and automatic enhancement for hierarchical taxonomies

  • Author/Authors

    Ghassan Beydoun، نويسنده , , Francisco Garc?a-S?nchez، نويسنده , , Cristin M. Vincent-Torres، نويسنده , , Antonio A. Lopez-Lorca، نويسنده , , Rodrigo Mart?nez-Béjar، نويسنده ,

  • Issue Information
    دوماهنامه با شماره پیاپی سال 2013
  • Pages
    16
  • From page
    67
  • To page
    82
  • Abstract
    Taxonomies enable organising information in a human–machine understandable form, but constructing them for reuse and maintainability remains difficult. The paper presents a formal underpinning to provide quality metrics for a taxonomy under development. It proposes a methodology for semi-automatic building of maintainable taxonomies and outlines key features of the knowledge engineering context where the metrics and methodology are most suitable. The strength of the approach presented is that it is applied during the actual construction of the taxonomy. Users provide terms to describe different domain elements, as well as their attributes, and methodology uses metrics to assess the quality of this input. Changes according to given quality constraints are then proposed during the actual development of the taxonomy.
  • Keywords
    Incremental knowledge development , Ontology Evaluation , Taxonomies , Data models , Knowledge monitoring
  • Journal title
    Information Processing and Management
  • Serial Year
    2013
  • Journal title
    Information Processing and Management
  • Record number

    1229328