• DocumentCode
    1867100
  • Title

    Partitioning of ontologies driven by a structure-based approach

  • Author

    Amato, F. ; De Santo, A. ; Moscato, V. ; Persia, F. ; Picariello, A. ; Poccia, S.R.

  • Author_Institution
    Dip. di Ing. Elettr. e Tecnol. dell´Inf., Univ. of Naples “Federico II”, Naples, Italy
  • fYear
    2015
  • fDate
    7-9 Feb. 2015
  • Firstpage
    320
  • Lastpage
    323
  • Abstract
    In this paper, we propose a novel structure-based partitioning algorithm able to break a large ontology into different modules related to specific topics for the domain of interest. In particular, we leverage the topological properties of the ontology graph and exploit several techniques derived from Network Analysis to produce an effective partitioning without considering any information about semantics of ontology relationships. An automated partitioning tool has been developed and several preliminary experiments have been conducted to validate the effectiveness of our approach with respect to other techniques.
  • Keywords
    graph theory; ontologies (artificial intelligence); topology; automated partitioning tool; network analysis; ontologies partitioning; ontology graph; ontology relationships; structure-based approach; structure-based partitioning algorithm; topological properties; Ions; Ontologies;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Semantic Computing (ICSC), 2015 IEEE International Conference on
  • Conference_Location
    Anaheim, CA
  • Type

    conf

  • DOI
    10.1109/ICOSC.2015.7050827
  • Filename
    7050827