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ISCI
2007
99views more  ISCI 2007»
13 years 5 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
DAWAK
2004
Springer
13 years 11 months ago
Algorithms for Discovery of Frequent Superset, Rather than Frequent Subset
Abstract. In this paper, we propose a novel mining task: mining frequent superset from the database of itemsets that is useful in bioinformatics, e-learning systems, jobshop schedu...
Zhung-Xun Liao, Man-Kwan Shan
RCIS
2010
13 years 4 months ago
A Tree-based Approach for Efficiently Mining Approximate Frequent Itemsets
—The strategies for mining frequent itemsets, which is the essential part of discovering association rules, have been widely studied over the last decade. In real-world datasets,...
Jia-Ling Koh, Yi-Lang Tu
DMIN
2007
158views Data Mining» more  DMIN 2007»
13 years 7 months ago
Mining Frequent Itemsets Using Re-Usable Data Structure
- Several algorithms have been introduced for mining frequent itemsets. The recent datasettransformation approach suffers either from the possible increasing in the number of struc...
Mohamed Yakout, Alaaeldin M. Hafez, Hussein Aly
ICDM
2003
IEEE
140views Data Mining» more  ICDM 2003»
13 years 11 months ago
Mining Frequent Itemsets in Distributed and Dynamic Databases
Traditional methods for frequent itemset mining typically assume that data is centralized and static. Such methods impose excessive communication overhead when data is distributed...
Matthew Eric Otey, Chao Wang, Srinivasan Parthasar...