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» Discovering Associations in XML Data
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KDD
2006
ACM
130views Data Mining» more  KDD 2006»
15 years 9 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
83
Voted
DASFAA
2003
IEEE
106views Database» more  DASFAA 2003»
15 years 2 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
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
KDD
2003
ACM
175views Data Mining» more  KDD 2003»
15 years 9 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
15 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