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BNCOD
2003
127views Database» more  BNCOD 2003»
14 years 11 months ago
Performance Evaluation and Analysis of K-Way Join Variants for Association Rule Mining
Data mining aims at discovering important and previously unknown patterns from the dataset in the underlying database. Database mining performs mining directly on data stored in r...
P. Mishra, Sharma Chakravarthy
ISMIS
2005
Springer
15 years 3 months ago
Mining and Filtering Multi-level Spatial Association Rules with ARES
In spatial data mining, a common task is the discovery of spatial association rules from spatial databases. We propose a distributed system, named ARES that takes advantage of the ...
Annalisa Appice, Margherita Berardi, Michelangelo ...
JIPS
2008
116views more  JIPS 2008»
14 years 9 months ago
An Empirical Study of Qualities of Association Rules from a Statistical View Point
: Minimum support and confidence have been used as criteria for generating association rules in all association rule mining algorithms. These criteria have their natural appeals, s...
Maryann Dorn, Wen-Chi Hou, Dunren Che, Zhewei Jian...
HAIS
2009
Springer
15 years 1 months ago
Evolutionary Extraction of Association Rules: A Preliminary Study on their Effectiveness
Abstract. Data Mining is most commonly used in attempts to induce association rules from transaction data. Most previous studies focused on binaryvalued transactions, however the d...
Nicolò Flugy Papè, Jesús Alca...
FUZZIEEE
2007
IEEE
15 years 4 months ago
Genetic Learning of Membership Functions for Mining Fuzzy Association Rules
— Data mining is most commonly used in attempts to induce association rules from transaction data. Most previous studies focused on binary-valued transaction data. Transaction da...
Rafael Alcalá, Jesús Alcalá-F...