Finding important vocabulary within ontology

  • Authors:

  • Xiang Zhang;Hongda Li;Yuzhong Qu

  • Affiliations:

  • Department of Computer Science and Engineering, Southeast University, Nanjing, P.R China;Department of Computer Science and Engineering, Southeast University, Nanjing, P.R China;Department of Computer Science and Engineering, Southeast University, Nanjing, P.R China

  • Venue:
  • ASWC'06 Proceedings of the First Asian conference on The Semantic Web
  • Year:
  • 2006

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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.