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WIREs Data Mining Knowl Discov
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Filtered‐top‐ k association discovery

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Association mining has been one of the most intensively researched areas of data mining. However, direct uptake of the resulting technologies has been relatively low. This paper examines some of the reasons why the dominant paradigms in association mining have not lived up to their promise, and argues that a powerful alternative is provided by top‐k techniques coupled with appropriate statistical and other filtering. © 2011 John Wiley & Sons, Inc. WIREs Data Mining Knowl Discov 2011 1 183–192 DOI: 10.1002/widm.28

This article is categorized under:

  • Algorithmic Development > Association Rules
  • Algorithmic Development > Statistics
  • Technologies > Association Rules

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Algorithmic Development > Statistics
Technologies > Association Rules
Algorithmic Development > Association Rules

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