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文章基本信息

  • 标题:A Triadic Approach of Hierarchical Classes Analysis on Folksonomy Mining
  • 作者:Suk-Hyung Hwang
  • 期刊名称:International Journal of Computer Science and Network Security
  • 印刷版ISSN:1738-7906
  • 出版年度:2007
  • 卷号:7
  • 期号:8
  • 页码:193-198
  • 出版社:International Journal of Computer Science and Network Security
  • 摘要:As the number of tagged data on the Web is increased, there are many needs on the folksonomy-based systems to provide some proper functionalities, such as identifying user interests, recommending relevant resources or constructing ontologies for sharing and reusing tag data, etc. However, some proper data mining approaches to folksonomies are necessary to better understand their characteristics and extract valuable information from folksonomies. In this paper, we propose a triadic approach for mining folksonomies based on hierarchical classes analysis, and demonstrate how triadic elements of folksonomies can be analyzed and mined by applying the proposed approach. We also discuss how the results can be used for better understanding of the characteristics of folksonomies.
  • 关键词:Hierarchical Classes Analysis; Folksonomy; Ontology; Tagging
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