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IEAAIE
2009
Springer
13 years 6 months ago
Hiding Predictive Association Rules on Horizontally Distributed Data
Abstract. In this work, we propose two approaches of hiding predictive association rules where the data sets are horizontally distributed and owned by collaborative but non-trustin...
Shyue-Liang Wang, Ting-Zheng Lai, Tzung-Pei Hong, ...
DASFAA
2004
IEEE
125views Database» more  DASFAA 2004»
14 years 15 days ago
Reducing Communication Cost in a Privacy Preserving Distributed Association Rule Mining
Data mining is a process that analyzes voluminous digital data in order to discover hidden but useful patterns from digital data. However, discovery of such hidden patterns has sta...
Mafruz Zaman Ashrafi, David Taniar, Kate A. Smith
JCST
2008
119views more  JCST 2008»
13 years 8 months ago
Mining Frequent Generalized Itemsets and Generalized Association Rules Without Redundancy
This paper presents some new algorithms to efficiently mine max frequent generalized itemsets (g-itemsets) and essential generalized association rules (g-rules). These are compact ...
Daniel Kunkle, Donghui Zhang, Gene Cooperman
CIDM
2009
IEEE
14 years 3 months ago
An improved multiple minimum support based approach to mine rare association rules
Abstract—In this paper we have proposed an improved approach to extract rare association rules. Rare association rules are the association rules containing rare items. Rare items...
R. Uday Kiran, P. Krishna Reddy
DMKD
1997
ACM
198views Data Mining» more  DMKD 1997»
14 years 29 days ago
Clustering Based On Association Rule Hypergraphs
Clustering in data mining is a discovery process that groups a set of data such that the intracluster similarity is maximized and the intercluster similarity is minimized. These d...
Eui-Hong Han, George Karypis, Vipin Kumar, Bamshad...