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 formalization of these accelerated gradual itemsets, as well as evaluation criteria. It illustrates the relevance of the proposed approach on real data.
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Oudni, A., Lesot, MJ., Rifqi, M. (2014). Accelerating Effect of Attribute Variations: Accelerated Gradual Itemsets Extraction. In: Laurent, A., Strauss, O., Bouchon-Meunier, B., Yager, R.R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2014. Communications in Computer and Information Science, vol 443. Springer, Cham. https://doi.org/10.1007/978-3-319-08855-6_40
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DOI: https://doi.org/10.1007/978-3-319-08855-6_40
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08854-9
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