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
Link To Document