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title:
 
A Fuzzy Rule Mining Approach involving Absent Items
publication:
 
EUSFLAT
part of series:
  Advances in Intelligent Systems Research
pages:   275 - 282
DOI:
  To be assigned soon (how to use a DOI)
author(s):
 
Miguel Delgado, María-Dolores Ruiz, Daniel Sánchez and José-María Serrano
publication date:
 
July 2011
keywords:
 
Data mining, Fuzzy association rules, absence of items, negative rules.
abstract:
 
In this paper we present how to extract fuzzy association rules involving both the presence and the absence of items using a fuzzy rule mining procedure introduced by the authors in previous works. The rule mining procedure is based on the GUHA logical model, fuzzified via a recently proposed representation of gradualness. We present some results obtained with real datasets.
copyright:
 
© Atlantis Press. This article is distributed under the terms of the Creative Commons Attribution License, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited.
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