Fundamentals of association rules in data mining and knowledge discovery

  • Zhang S
  • Wu X
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Abstract

Association rule mining is one of the fundamental research topics in data mining and knowledge discovery that identifies interesting relationships between item-sets in datasets and predicts the associative and correlative behaviors for new data. Rooted in market basket analysis, there are a great number of techniques developed for association rule mining. They include frequent pattern discovery, interestingness, complex associations, and multiple data source mining. This paper introduces the up-to-date prevailing association rule mining methods and advocates the mining of complete association rules, including both positive and negative association rules. (C) 2011 John Wiley& Sons, Inc. WIREs DataMining Knowl Discov 2011 1 97-116 DOI:10.1002/widm.10

Author-supplied keywords

  • FREQUENT PATTERNS
  • LARGE DATABASES
  • SUPPORT

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Authors

  • S C Zhang

  • X D Wu

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