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Volumn 24, Issue 8, 2011, Pages 1214-1223

Privacy preserving data mining: A noise addition framework using a novel clustering technique

Author keywords

Clustering categorical values; Data mining; Data perturbation; Noise addition; Privacy analysis; Privacy preserving data mining

Indexed keywords

CLUSTERING CATEGORICAL VALUES; DATA PERTURBATION; NOISE ADDITION; PRIVACY ANALYSIS; PRIVACY PRESERVING DATA MINING;

EID: 80051474819     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2011.05.011     Document Type: Article
Times cited : (88)

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    • Ph.D. Thesis, School of Electrical Engineering and Computer Science, The University of Newcastle, Australia
    • M.Z. Islam, Privacy Preservation in Data Mining through Noise Addition, Ph.D. Thesis, School of Electrical Engineering and Computer Science, The University of Newcastle, Australia, 2008.
    • (2008) Privacy Preservation in Data Mining Through Noise Addition
    • Islam, M.Z.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.