2014
DOI: 10.1007/978-3-319-08855-6_40
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Accelerating Effect of Attribute Variations: Accelerated Gradual Itemsets Extraction

Abstract: Abstract. Gradual itemsets of the form "the more/less A, the more/less B" summarize data through the description of their internal tendencies, identified as correlation between attribute values. This paper proposes to enrich such gradual itemsets by taking into account an acceleration effect, leading to a new type of gradual itemset of the form "the more/less A increases, the more quickly B increases". It proposes an interpretation as convexity constraint imposed on the relation between A and B and a formaliza… Show more

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Cited by 3 publications
(3 citation statements)
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“…Accelerated gradual itemsets aim at extracting information in the form of correlations between attribute values by focusing on how fast the values of some attributes vary as compared to others [22]. This section briefly recalls their principle, formalization and the evaluation criterion of the acceleration effect.…”
Section: Accelerated Gradual Itemsetsmentioning
confidence: 99%
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“…Accelerated gradual itemsets aim at extracting information in the form of correlations between attribute values by focusing on how fast the values of some attributes vary as compared to others [22]. This section briefly recalls their principle, formalization and the evaluation criterion of the acceleration effect.…”
Section: Accelerated Gradual Itemsetsmentioning
confidence: 99%
“…The principle of acceleration is naturally understood as speed variation increase, which can be translated as a convexity constraint on the underlying function associating the considered attributes. This constraint can be modeled as an additional co-variation constraint, leading to the definition of a criterion called accelerated support to assess the validity of such accelerated gradual itemsets [22]. It is added to the evaluation of the gradual itemset through the classical gradual support defined in Equation 1.…”
Section: ) Principlementioning
confidence: 99%
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