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文章基本信息

  • 标题:Learning Ontology from Object-Relational Database
  • 作者:Andrejs Kaulins ; Arkady Borisov
  • 期刊名称:Information Technology and Management Science
  • 印刷版ISSN:2255-9086
  • 电子版ISSN:2255-9094
  • 出版年度:2015
  • 卷号:18
  • 期号:1
  • 页码:78-83
  • DOI:10.1515/itms-2015-0012
  • 语种:English
  • 出版社:Walter de Gruyter GmbH
  • 摘要:This article describes a method of transformation of object-relational model into ontology. The offered method uses learning rules for such complex data types as object tables and collections – arrays of a variable size, as well as nested tables. Object types and their transformation into ontologies are insufficiently considered in scientific literature. This fact served as motivation for the authors to investigate this issue and to write the article on this matter. In the beginning, we acquaint the reader with complex data types and object-oriented databases. Then we describe an algorithm of transformation of complex data types into ontologies. At the end of the article, some examples of ontologies described in the OWL language are given.
  • 关键词:Complex data types ; object-relational model ; ontology ; ontology learning
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