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Selecting Outstanding Patterns Based on Their Neighbourhood

Abstract : The purpose of pattern mining is to help experts understand their data. Following the assumption that an analyst expects neighbouring patterns to show similar behavior, we investigate the interestingness of a pattern given its neighborhood. We define a new way of selecting outstanding patterns, based on an order relation between patterns and a quality score. An outstanding pattern shows only small syntactic variations compared to its neighbors but deviates strongly in quality. Using several supervised quality measures, we show experimentally that only very few patterns turn out to be outstanding. We also illustrate our approach with patterns mined from molecular data.
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Contributor : Etienne Lehembre Connect in order to contact the contributor
Submitted on : Wednesday, May 4, 2022 - 9:34:24 AM
Last modification on : Saturday, June 25, 2022 - 9:57:38 AM
Long-term archiving on: : Friday, August 5, 2022 - 6:08:57 PM


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Etienne Lehembre, Ronan Bureau, Bruno Crémilleux, Bertrand Cuissart, Jean-Luc Lamotte, et al.. Selecting Outstanding Patterns Based on Their Neighbourhood. Tassadit Bouadi; Elisa Fromont; Eyke Hüllermeier. Advances in Intelligent Data Analysis XX. 20th International Symposium on Intelligent Data Analysis, IDA 2022, Rennes, France, April 20–22, 2022, Proceedings, 13205, Springer International Publishing, pp.185-198, 2022, Lecture Notes in Computer Science, 978-3-031-01332-4. ⟨10.1007/978-3-031-01333-1_15⟩. ⟨hal-03658500⟩



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