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Finding Important Vocabulary Within Ontology

  • Xiang Zhang
  • Hongda Li
  • Yuzhong Qu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4185)

Abstract

In current Semantic Web community, some researches have been done on ranking ontologies, while very little is paid to ranking vocabularies within ontology. However, finding important vocabularies within a given ontology will bring benefits to ontology indexing, ontology understanding and even ranking vocabularies from a global view. In this paper, Vocabulary Dependency Graph (VDG) is proposed to model the dependencies among vocabularies within an ontology, and Textual Score of Vocabulary (TSV) is established based on the idea of virtual documents. And then a Double Focused PageRank algorithm is applied on VDG and TSV to rank vocabulary within ontology. Primary experiments demonstrate that our approach turns out to be useful in finding important vocabularies within ontology.

Keywords

Ranking Algorithm Linguistic Information Class Hierarchy Ranking Scheme Blank Node 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Xiang Zhang
    • 1
  • Hongda Li
    • 1
  • Yuzhong Qu
    • 1
  1. 1.Department of Computer Science and EngineeringSoutheast UniversityNanjingP.R. China

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