Privacy-preservation techniques in data mining

Chunhua Su, Jianying Zhou, Feng Bao, Guilin Wang, Kouichi Sakurai

研究成果: Chapter in Book/Report/Conference proceedingChapter


In today’s information age, data collection is ubiquitous, and every transaction is recorded somewhere. The resulting data sets can consist of terabytes or even petabytes of data, so efficiency and scalability is the primary consideration of most data-mining algorithms. Data mining is becoming increasingly common in both the private and public sectors. Industries, such as banking, insurance, medicine, and retailing, commonly use data mining to reduce costs, enhance research, and increase sales. In the public sector, data-mining applications initially were used as a means to detect fraud and waste, but have grown to also be used for purposes, such as measuring and improving program performance.

ホスト出版物のタイトルDigital Privacy
ホスト出版物のサブタイトルTheory, Technologies, and Practices
出版者CRC Press
出版物ステータス出版済み - 1 1 2007

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Economics, Econometrics and Finance(all)
  • Business, Management and Accounting(all)

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  • これを引用

    Su, C., Zhou, J., Bao, F., Wang, G., & Sakurai, K. (2007). Privacy-preservation techniques in data mining. : Digital Privacy: Theory, Technologies, and Practices (pp. 187-226). CRC Press.