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» Mining Association Rules: Anti-Skew Algorithms
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ICDM
2005
IEEE
139views Data Mining» more  ICDM 2005»
14 years 1 months ago
Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and Approximation
In order to generate synthetic basket data sets for better benchmark testing, it is important to integrate characteristics from real-life databases into the synthetic basket data ...
Yongge Wang, Xintao Wu
RCIS
2010
13 years 6 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
IDEAL
2003
Springer
14 years 24 days ago
Improving the Efficiency of Frequent Pattern Mining by Compact Data Structure Design
Mining frequent patterns has been a topic of active research because it is computationally the most expensive step in association rule discovery. In this paper, we discuss the use ...
Raj P. Gopalan, Yudho Giri Sucahyo
IQIS
2004
ACM
14 years 1 months ago
Mining for Patterns in Contradictory Data
Information integration is often faced with the problem that different data sources represent the same set of the real-world objects, but give conflicting values for specific prop...
Heiko Müller, Ulf Leser, Johann Christoph Fre...
KDD
2004
ACM
160views Data Mining» more  KDD 2004»
14 years 8 months ago
k-TTP: a new privacy model for large-scale distributed environments
Secure multiparty computation allows parties to jointly compute a function of their private inputs without revealing anything but the output. Theoretical results [2] provide a gen...
Bobi Gilburd, Assaf Schuster, Ran Wolff