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ISCI
2007
99views more  ISCI 2007»
13 years 7 months ago
Privacy-preserving algorithms for distributed mining of frequent itemsets
Standard algorithms for association rule mining are based on identification of frequent itemsets. In this paper, we study how to maintain privacy in distributed mining of frequen...
Sheng Zhong
CIKM
2009
Springer
14 years 2 months ago
Mining frequent itemsets in time-varying data streams
Mining frequent itemsets in data streams is beneficial to many real-world applications but is also a challenging task since data streams are unbounded and have high arrival rates...
Yingying Tao, M. Tamer Özsu
KDD
2002
ACM
128views Data Mining» more  KDD 2002»
14 years 8 months ago
Privacy preserving mining of association rules
We present a framework for mining association rules from transactions consisting of categorical items where the data has been randomized to preserve privacy of individual transact...
Alexandre V. Evfimievski, Ramakrishnan Srikant, Ra...
KES
2008
Springer
13 years 6 months ago
Fast Cryptographic Privacy Preserving Association Rules Mining on Distributed Homogenous Data Base
Privacy is one of the most important properties of an information system must satisfy. In which systems the need to share information among different, not trusted entities, the pro...
Mahmoud Hussein, Ashraf El-Sisi, Nabil A. Ismail
FIMI
2004
239views Data Mining» more  FIMI 2004»
13 years 9 months ago
LCM ver. 2: Efficient Mining Algorithms for Frequent/Closed/Maximal Itemsets
: For a transaction database, a frequent itemset is an itemset included in at least a specified number of transactions. A frequent itemset P is maximal if P is included in no other...
Takeaki Uno, Masashi Kiyomi, Hiroki Arimura