Privacy preserving data mining

著者

    • Vaidya, Jaideep
    • Clifton, Christopher W.
    • Zhu, Yu Michael

書誌事項

Privacy preserving data mining

Jaideep Vaidya, Christopher W. Clifton, Yu Michael Zhu

(Advances in information security, 19)

Springer, c2006

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内容説明・目次

内容説明

Privacy preserving data mining implies the "mining" of knowledge from distributed data without violating the privacy of the individual/corporations involved in contributing the data. This volume provides a comprehensive overview of available approaches, techniques and open problems in privacy preserving data mining. Crystallizing much of the underlying foundation, the book aims to inspire further research in this new and growing area. Privacy Preserving Data Mining is intended to be accessible to industry practitioners and policy makers, to help inform future decision making and legislation, and to serve as a useful technical reference.

目次

Privacy and Data Mining.- What is Privacy?.- Solution Approaches / Problems.- Predictive Modeling for Classification.- Predictive Modeling for Regression.- Finding Patterns and Rules (Association Rules).- Descriptive Modeling (Clustering, Outlier Detection).- Future Research - Problems remaining.

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詳細情報

  • NII書誌ID(NCID)
    BA75425435
  • ISBN
    • 0387258868
  • 出版国コード
    us
  • タイトル言語コード
    eng
  • 本文言語コード
    eng
  • 出版地
    New York
  • ページ数/冊数
    120 p.
  • 大きさ
    25 cm
  • 親書誌ID
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