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HAIS
2011
Springer
13 years 1 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
2007
IEEE
134views Data Mining» more  ICDM 2007»
14 years 4 months ago
On Regional Association Rule Scoping
A special challenge for spatial data mining is that information is not distributed uniformly in spatial data sets. Consequently, the discovery of regional knowledge is of fundamen...
Wei Ding 0003, Christoph F. Eick, Xiaojing Yuan, J...
CSE
2008
IEEE
13 years 12 months ago
ACN: An Associative Classifier with Negative Rules
Classification using association rules has added a new dimension to the ongoing research for accurate classifiers. Over the years, a number of associative classifiers based on pos...
Gourab Kundu, Md. Monirul Islam, Sirajum Munir, Md...
KES
2004
Springer
14 years 3 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...
SIGMOD
1997
ACM
148views Database» more  SIGMOD 1997»
14 years 2 months ago
Beyond Market Baskets: Generalizing Association Rules to Correlations
One of the most well-studied problems in data mining is mining for association rules in market basket data. Association rules, whose significance is measured via support and confi...
Sergey Brin, Rajeev Motwani, Craig Silverstein