• DocumentCode
    2918742
  • Title

    Evaluation Metrics for Ontology Complexity and Evolution Analysis

  • Author

    YANG, Zhe ; Zhang, Dalu ; YE, Chuan

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Tongji Univ., Shanghai
  • fYear
    2006
  • fDate
    Oct. 2006
  • Firstpage
    162
  • Lastpage
    170
  • Abstract
    With the tremendous development in size, the complexity of ontology increases. Thus ontology evaluation becomes extremely important for developers to determine the fundamental characteristics of ontologies in order to improve the quality, estimate cost and reduce future maintenance. Our research examines the concepts and their hierarchy in conceptual model, the common feature of the most ontologies, which reflects the fundamental complexity. We suggest a well-defined metrics suite of complexity, which mainly examine the quantity, ratio and correlativity of concepts and relationships, to evaluate ontologies from the viewpoint of complexity and its evolution. In the study, we measure three ontologies in GO to verify our metrics. The results indicate that this metrics suite works well, and the biological process ontology is the most complex one from the view of complexity, and the molecular function ontology is the unsteadiest one from the view of evolution
  • Keywords
    ontologies (artificial intelligence); evolution analysis; ontology complexity; ontology evaluation metrics; Biological processes; Collaborative work; Computer science; Costs; Displays; Engineering management; Evolution (biology); International collaboration; Ontologies; Peer to peer computing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    e-Business Engineering, 2006. ICEBE '06. IEEE International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    0-7695-2645-4
  • Type

    conf

  • DOI
    10.1109/ICEBE.2006.48
  • Filename
    4031647