• DocumentCode
    147249
  • Title

    Privacy preservation algorithm in data mining for CRM systems

  • Author

    Virupaksha, Shashidhar ; Sahoo, G. ; Vasudevan, Ananthasayanam

  • Author_Institution
    Birla Inst. of Technol., Ranchi, India
  • fYear
    2014
  • fDate
    3-5 April 2014
  • Firstpage
    1615
  • Lastpage
    1619
  • Abstract
    Organizations have a huge customer base and thus they use data mining tools to study their customers. However there is risk of sensitive information about individuals which can be gained also during this process. Hence data that is used for data mining has to be protected. There are some privacy protection algorithms which ensure privacy and protect data. These algorithms preserve privacy but data mining results significantly. In this paper we propose a clustering based noise addition that not only preserves privacy but also ensures effective data mining. Data characteristics are identified using clustering technique and noise is added within the clusters thus retaining the data characteristics.
  • Keywords
    customer relationship management; data mining; data privacy; pattern clustering; CRM systems; clustering based noise addition; clustering technique; customer base; customer relationship management; data characteristics; data mining tools; data privacy; data protection; organizations; privacy preservation algorithm; privacy protection algorithms; sensitive information; Clustering algorithms; Data privacy; Diseases; Privacy; Remuneration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications and Signal Processing (ICCSP), 2014 International Conference on
  • Conference_Location
    Melmaruvathur
  • Print_ISBN
    978-1-4799-3357-0
  • Type

    conf

  • DOI
    10.1109/ICCSP.2014.6950121
  • Filename
    6950121