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» Efficient Algorithms for Discovering Association Rules
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KDD
2005
ACM
103views Data Mining» more  KDD 2005»
14 years 9 months ago
Fast discovery of unexpected patterns in data, relative to a Bayesian network
We consider a model in which background knowledge on a given domain of interest is available in terms of a Bayesian network, in addition to a large database. The mining problem is...
Szymon Jaroszewicz, Tobias Scheffer
ASC
2011
13 years 3 months ago
A rough set approach to multiple dataset analysis
In the area of data mining, the discovery of valuable changes and connections (e.g., causality) from multiple data sets has been recognized as an important issue. This issue essen...
Ken Kaneiwa
IDA
2009
Springer
13 years 6 months ago
Efficient Vertical Mining of Frequent Closures and Generators
Abstract. The effective construction of many association rule bases requires the computation of both frequent closed and frequent generator itemsets (FCIs/FGs). However, only few m...
Laszlo Szathmary, Petko Valtchev, Amedeo Napoli, R...
CIKM
2001
Springer
14 years 13 days ago
Sliding-Window Filtering: An Efficient Algorithm for Incremental Mining
We explore in this paper an effective sliding-window filtering (abbreviatedly as SWF) algorithm for incremental mining of association rules. In essence, by partitioning a transact...
Chang-Hung Lee, Cheng-Ru Lin, Ming-Syan Chen
JUCS
2007
118views more  JUCS 2007»
13 years 8 months ago
A Model of Immune Gene Expression Programming for Rule Mining
: Rule mining is an important issue in data mining. To address it, a novel Immune Gene Expression Programming (IGEP) model was proposed. Concepts of rule, gene, immune cell, and an...
Tao Zeng, Changjie Tang, Yong Xiang, Peng Chen, Yi...