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2002
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Generating an informative cover for association rules

9 years 10 months ago
Generating an informative cover for association rules
Mining association rules may generate a large numbers of rules making the results hard to analyze manually. Pasquier et al. have discussed the generation of GuiguesDuquenne–Luxenburger basis (GD-L basis). Using a similar approach, we introduce a new rule of inference and define the notion of association rules cover as a minimal set of rules that are non-redundant with respect to this new rule of inference. Our experimental results (obtained using both synthetic and real data sets) show that our covers are smaller than the GD-L basis and they are computed in time that is comparable to the classic Apriori algorithm for generating rules.
Laurentiu Cristofor, Dan A. Simovici
Added 14 Jul 2010
Updated 14 Jul 2010
Type Conference
Year 2002
Where ICDM
Authors Laurentiu Cristofor, Dan A. Simovici
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