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The association rules, discovered by traditional support–confidence based algorithms, provide us with concise statements of potentially useful information hidden in databases. However, only considering the constraints of minimum support and minimum confidence is far from satisfying in many cases. In this paper, we propose a fuzzy method to formulate how interesting an association rule may be. It is...
Association rule mining is concerned with the discovery of interesting association relationships hidden in databases. Traditional algorithms are only considering the constraints of minimum support and minimum confidence. However, sometimes it is essential to find stronger association rules for decision makers possessing inadequate resources, and sometimes less strong rules are needed. In this paper,...
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