Abstract
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.
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Nguyen, PK., Nguyen, TT. (2011). Evaluation the Objectivity Measurement of Frequent Patterns. In: Ao, SI., Amouzegar, M., Rieger, B. (eds) Intelligent Automation and Systems Engineering. Lecture Notes in Electrical Engineering, vol 103. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-0373-9_21
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DOI: https://doi.org/10.1007/978-1-4614-0373-9_21
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