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SBACPAD
2003
IEEE
180views Hardware» more  SBACPAD 2003»
15 years 2 months ago
New Parallel Algorithms for Frequent Itemset Mining in Very Large Databases
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
SOFTVIS
2005
ACM
15 years 3 months ago
Visual data mining in software archives
Software archives contain historical information about the development process of a software system. Using data mining techniques rules can be extracted from these archives. In th...
Michael Burch, Stephan Diehl, Peter Weißgerb...
ICDM
2005
IEEE
177views Data Mining» more  ICDM 2005»
15 years 3 months ago
Average Number of Frequent (Closed) Patterns in Bernouilli and Markovian Databases
In data mining, enumerate the frequent or the closed patterns is often the first difficult task leading to the association rules discovery. The number of these patterns represen...
Loïck Lhote, François Rioult, Arnaud S...
SAC
2010
ACM
14 years 4 months ago
A study on interestingness measures for associative classifiers
Associative classification is a rule-based approach to classify data relying on association rule mining by discovering associations between a set of features and a class label. Su...
Mojdeh Jalali Heravi, Osmar R. Zaïane
KES
2004
Springer
15 years 3 months ago
FIT: A Fast Algorithm for Discovering Frequent Itemsets in Large Databases
Association rule mining is an important data mining problem that has been studied extensively. In this paper, a simple but Fast algorithm for Intersecting attribute lists using a ...
Jun Luo, Sanguthevar Rajasekaran