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» Mining Multi-Dimensional Quantitative Associations
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HAIS
2009
Springer
13 years 11 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...
HAIS
2011
Springer
12 years 11 months ago
Evolving Temporal Fuzzy Association Rules from Quantitative Data with a Multi-Objective Evolutionary Algorithm
A novel method for mining association rules that are both quantitative and temporal using a multi-objective evolutionary algorithm is presented. This method successfully identifie...
Stephen G. Matthews, Mario A. Góngora, Adri...
ICDM
2008
IEEE
109views Data Mining» more  ICDM 2008»
14 years 2 months ago
Quantitative Association Analysis Using Tree Hierarchies
Association analysis arises in many important applications such as bioinformatics and business intelligence. Given a large collection of measurements over a set of samples, associ...
Feng Pan, Lynda Yang, Leonard McMillan, Fernando P...
CIB
2002
100views more  CIB 2002»
13 years 7 months ago
Web-log Mining for Quantitative Temporal-Event Prediction
The web log data embed much of web users' browsing behavior. From the web logs, one can discover patterns that predict the users' future requests based on their current b...
Qiang Yang, Hui Wang, Wei Zhang
FUZZIEEE
2007
IEEE
14 years 1 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...