Identifying Potentially Important Concepts and Relations in an Ontology

  • Gang Wu
  • Juanzi Li
  • Ling Feng
  • Kehong Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5318)


More and more ontologies have been published and used widely on the web. In order to make good use of an ontology, especially a new and complex ontology, we need methods to help understand it first. Identifying potentially important concepts and relations in an ontology is an intuitive but challenging method. In this paper, we first define four features for potentially important concepts and relation from the ontological structural point of view. Then a simple yet effective Concept-And-Relation-Ranking (CARRank) algorithm is proposed to simultaneously rank the importance of concepts and relations. Different from the traditional ranking methods, the importance of concepts and the weights of relations reinforce one another in CARRank in an iterative manner. Such an iterative process is proved to be convergent both in principle and by experiments. Our experimental results show that CARRank has a similar convergent speed as the PageRank-like algorithms, but a more reasonable ranking result.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Gang Wu
    • 1
    • 2
  • Juanzi Li
    • 1
  • Ling Feng
    • 1
  • Kehong Wang
    • 1
  1. 1.Department of Computer ScienceTsinghua UniversityBeijingP.R. China
  2. 2.Department of Computer ScienceSoutheastern UniversityNanjingP.R. China

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