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文章基本信息

  • 标题:PPKM: Preserving Privacy in Knowledge Management
  • 本地全文:下载
  • 作者:N. Maheswari ; K. Duraiswamy
  • 期刊名称:International Business Research
  • 印刷版ISSN:1913-9004
  • 电子版ISSN:1913-9012
  • 出版年度:2009
  • 卷号:2
  • 期号:2
  • 页码:182
  • DOI:10.5539/ibr.v2n2p182
  • 出版社:Canadian Center of Science and Education
  • 摘要:

    This paper discusses the techniques that support the extraction, sharing, and utilization of knowledge for collaborative problem solving applications. A system framework is proposed for secure knowledge management, called PPKM, which in addition to provide standard security mechanisms such as access control, will possess crucial feature, namely privacy-preservation , where privacy-preservation means that the knowledge extraction process should not compromise the privacy of the source data. This framework is explained by elaborating on its components and their relationship to existing techniques such as database, data perturbation, rule hiding, data mining, and machine learning.

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