The Research on Measure Method of Association Rules Mining

  • Gao Yongmei
  • Published 2015

Abstract

Data mining receives much attention from artificial intelligence and databases, and the association rule is one of the most important research fields of data mining. In this paper, the advantages and disadvantages of the specific indicators of objective measure, subjective measure, and association rule based on statistical perspective are discussed. Some indicators of statistical perspective are adopted to measure the association rules, which can effectively solve the problems of association rules. Next, a further verification of the advantage and disadvantages of the indicators is made by the combination of the theory and application, a new measure frame is put forward as well. Then, the dynamic association rules are analyzed through making a comparative analysis in the following four aspects: the traditional association analysis without the life cycle, the association rules with the life cycle, the weighted dynamic association rules and the weighted dynamic association rules weighted by the consumption amount, showing the influence of timeliness on association rules analysis, and thus effectively mining some rules with low support in global period but high support in a certain period.

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Cite this paper

@inproceedings{Yongmei2015TheRO, title={The Research on Measure Method of Association Rules Mining}, author={Gao Yongmei}, year={2015} }