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基于分治策略的MASK算法的改进 被引量：1

A improved MASK algorithm by using divide and conquer strategy
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摘要 如何保护私有信息或敏感知识在挖掘过程中不被泄露,同时能得到较为准确的挖掘结果,目前已经成为数据挖掘研究中的一个很有意义的研究课题。本文在MASK算法的基础上提出一种改进的保护输入隐私的MASK算法。相对于MASK算法,改进的MASK算法在保证较好的输入数据隐私度和挖掘结果的准确度的同时,其运行效率也得到了明显提高。 There has been a meaningful research problem that how to protect privacy or sensitive information from leaking during data mining process ,meanwhile obtain accurate result.This paper presents a improved MASK algorithm. The improved MASK algorithm presented in this paper can simultaneously meet satisfactory privacy and accuracy,while the runtime efficiency is advanced obviously compared with MASK algorithm.
作者 武振华 刘山 崔健国
机构地区 中国民航大学计算机学院
出处 《微计算机信息》 2009年第36期78-80,共3页 Control & Automation
关键词 隐私保护 MASK算法 分治策略 时间效率 Privacy-Preserve MASK algorithm divide and conquer strategy runtime efficiency
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
  • 相关文献

参考文献7

  • 1Verykios VS, Bertino E, Fovino IN, Provenza LP, Saygin Y, Theodoridis Y. State-of-the-Art in privacy preserving data mining. SIGMOD Record, 2004,33(1):50-57.
  • 2Han J, Kamber M. Data Mining: Concepts and Techniques. Beijing: China Machine Press, 2001.
  • 3陈芸,张伟.隐私保护数据挖掘方法的研究[J].微计算机信息,2006(07X):239-241. 被引量：7
  • 4Rizvi S, Haritsa J R. Maintaining Data Privacy in Association Rule Mining [C]. Proc. of 28th Int. Conf. on Very Large Databases, 2002.
  • 5D. Agrawal and C. Aggarwal, \On the Design and Quanti_cation of Privacy Preserving Data Mining Algorithms", Proc. of 20thACM Symp. on Principles of Database Systems (PODS), May 2001.
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  • 7Agrawal S, Krishnan V, Haritsa JR. On addressing efficiency concerns in privacy-preserving mining. In: Lee YJ, Li JZ, Whang KY, Lee D, eds. Proc. of the 9th Int'l Conf. on Database Systems for Advanced Applications. LNCS 2973, Jeju Island: Springer- Verlag,2004. 113-124.

二级参考文献6

  • 1张特来,刘万军.数据挖掘在供应管理中的应用[J].微计算机信息,2005,21(10X):182-183. 被引量：11
  • 2Han J，Kamber M．Data Mining：Concepts and Techniques．[M]．北京：机械工业出版社，2001-08
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共引文献6

同被引文献7

  • 1黄毅群,卢正鼎,胡和平,李瑞轩.分布式环境下保持隐私的关联规则挖掘算法[J].计算机工程,2006,32(13):12-14. 被引量：7
  • 2陈晓明,李军怀,彭军,刘海玲,张璟.隐私保护数据挖掘算法综述[J].计算机科学,2007,34(6):183-186. 被引量：16
  • 3Verykios V S, Bertino E, Fovino I N, et al. State-of-the- Art in privacy preserving datamining [ J ]. SIGMOD Record ,2004,33 ( 1 ) :50 - 57.
  • 4Rizvi S, Haritsa J R. Maintaining Data Privacy in Association Rule Mining [ C ]//Proc. of 28^th Int. Conf. On Very Large Databases,USA: [s. n. ] ,2002.
  • 5Agrawal R,Imielinski T,Swami A. Mining association rules between sets of items in large databases [ C ]//Proc. Of ACM SIGMOD Intl. Conf. On management of data. USA: [ s. n. ] ,1993.
  • 6Agrawal S, Krishnan V, Haritsa J R. On addressing efficiency concerns in privacy-preserving minning [ M ]// Lee Y J,Li J Z,Whang K Y,et al. Proc. of the 9th Intl. Conf. On Database Systems for Advanced Applications. LNCX 2973. Jeju Island : Springer-Verlag, 2004 : 113 - 124.
  • 7Alexey Pryakhin, Matthias Schubert, Arthur Zimek, et al. Future trends in data mining [ J ]. Data Min Knowl Disc ,2007,15:87 - 97.

引证文献1

二级引证文献7

微计算机信息
2009年 第36期

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