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» Discovering Associations in XML Data
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KDD
2006
ACM
130views Data Mining» more  KDD 2006»
14 years 10 months ago
Discovering significant rules
In many applications, association rules will only be interesting if they represent non-trivial correlations between all constituent items. Numerous techniques have been developed ...
Geoffrey I. Webb
DASFAA
2003
IEEE
106views Database» more  DASFAA 2003»
14 years 3 months ago
Discovering Direct and Indirect Matches for Schema Elements
Automating schema matching is challenging. Previous approaches (e.g. [MBR01, DDH01]) to automating schema matching focus on computing direct element matches between two schemas. S...
Li Xu, David W. Embley
SAC
2010
ACM
13 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
KDD
2003
ACM
175views Data Mining» more  KDD 2003»
14 years 10 months ago
Weighted Association Rule Mining using weighted support and significance framework
We address the issues of discovering significant binary relationships in transaction datasets in a weighted setting. Traditional model of association rule mining is adapted to han...
Feng Tao, Fionn Murtagh, Mohsen Farid
CIBCB
2007
IEEE
14 years 1 months ago
Associative Artificial Neural Network for Discovery of Highly Correlated Gene Groups Based on Gene Ontology and Gene Expression
Abstract-- The advance of high-throughput experimental technologies poses continuous challenges to computational data analysis in functional and comparative genomics studies. Gene ...
Ji He, Xinbin Dai, Xuechun Zhao