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SIGMOD
1996
ACM
110views Database» more  SIGMOD 1996»
13 years 9 months ago
Mining Quantitative Association Rules in Large Relational Tables
We introduce the problem of mining association rules in large relational tables containing both quantitative and categorical attributes. An example of such an association might be...
Ramakrishnan Srikant, Rakesh Agrawal
KES
2004
Springer
13 years 10 months ago
Mining Positive and Negative Fuzzy Association Rules
While traditional algorithms concern positive associations between binary or quantitative attributes of databases, this paper focuses on mining both positive and negative fuzzy ass...
Peng Yan, Guoqing Chen, Chris Cornelis, Martine De...
ICDE
2007
IEEE
129views Database» more  ICDE 2007»
13 years 11 months ago
Ontology-driven Rule Generalization and Categorization for Market Data
—Radio Frequency Identification (RFID) is an emerging technique that can significantly enhance supply chain processes and deliver customer service improvements. RFID provides use...
Dongwoo Won, Dennis McLeod
DATAMINE
1998
126views more  DATAMINE 1998»
13 years 4 months ago
An Extension to SQL for Mining Association Rules
Data mining evolved as a collection of applicative problems and efficient solution algorithms relative to rather peculiar problems, all focused on the discovery of relevant infor...
Rosa Meo, Giuseppe Psaila, Stefano Ceri
KDD
2003
ACM
175views Data Mining» more  KDD 2003»
14 years 5 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