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.
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© 2006 Springer-Verlag Berlin Heidelberg
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Zhang, X., Li, H., Qu, Y. (2006). Finding Important Vocabulary Within Ontology. In: Mizoguchi, R., Shi, Z., Giunchiglia, F. (eds) The Semantic Web – ASWC 2006. ASWC 2006. Lecture Notes in Computer Science, vol 4185. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11836025_11
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DOI: https://doi.org/10.1007/11836025_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-38329-1
Online ISBN: 978-3-540-38331-4
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