Abstract
Association rule mining is an important component of data mining. In the last years a great number of algorithms have been proposed with the objective of solving the obstacles presented in the generation of association rules. In this work, a new graph based algorithm for associative rule mining which has so many advantages over the existing methods is proposed. It can be used to improve decision making in a wide variety of applications such as: market basket analysis, medical diagnosis, bio-medical literature, protein sequences, census data, logistic regression, fraud detection in web, CRM of credit card business etc.
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