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Volumn E89-D, Issue 11, 2006, Pages 2739-2747

Mining frequent patterns securely in distributed system

Author keywords

Data mining; Distributed computing; Performance evaluation; Privacy preserving

Indexed keywords

DISTRIBUTED COMPUTER SYSTEMS; SECURITY OF DATA; SOCIETIES AND INSTITUTIONS;

EID: 33845565062     PISSN: 09168532     EISSN: 17451361     Source Type: Journal    
DOI: 10.1093/ietisy/e89-d.11.2739     Document Type: Article
Times cited : (7)

References (23)
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    • Privacy-preserving distributed mining of association rules on horizontally partitioned data
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    • Onion routing for anonymous and private Internet connections
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    • Goldschlag, D.1    Reed, M.2    Syverson, P.3
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    • Privacy preserving data mining
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    • Lindell, Y.1    Pinkas, B.2
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    • Tools for privacy preserving distributed data mining
    • C. Clifton, M. Kantarcioglou, X. Lin, and M.Y. Zhu, "Tools for privacy preserving distributed data mining," SIGKDD Explorations, vol.4, no.2, pp.28-34, 2002.
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    • Clifton, C.1    Kantarcioglou, M.2    Lin, X.3    Zhu, M.Y.4
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    • Efficient, accurate and privacy-preserving data mining for frequent itemsets in distributed databases
    • Manaus, Amazonas, Brazil
    • A.A. Veloso, W. Meira, Jr., S. Parthasarathy, and M.B. Carvalho, "Efficient, accurate and privacy-preserving data mining for frequent itemsets in distributed databases," Proc. 18th Brazilian Symposium on Databases, pp.281-292, Manaus, Amazonas, Brazil, 2003.
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    • Mining frequent patterns without candidate generation: A frequent pattern tree approach
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    • Han, J.1    Pei, J.2    Yin, Y.3    Mao, R.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.