Evaluation the Objectivity Measurement of Frequent Patterns

  • Phi-Khu Nguyen
  • Thanh-Trung Nguyen
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 103)


Frequent pattern mining is a basic problem in data mining and knowledge discovery. The discovered patterns can be used as the input for analyzing association rules, mining sequential patterns, recognizing clusters, and so on. However, there is a posed question that how is objectivity measurement of frequent patterns? Specifically, in market basket analysis problem to find out association rules, whether or not the frequent patterns discovered represent exactly the needs of all customers. Or, these frequent patterns were only created by a few customers with too many purchases. In this paper, a mathematical space will be introduced with some new related concepts and propositions to design a new algorithm answering the above questions.


Association Rule Frequent Pattern Boolean Matrix Representative Pattern Maximal Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Km20 Hanoi Highway – Quarter 6 – LinhTrung WardHo Chi MinhVietnam

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