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Conference Papers Year : 2022

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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Dates and versions

hal-03658500 , version 1 (04-05-2022)

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Etienne Lehembre, Ronan Bureau, Bruno Crémilleux, Bertrand Cuissart, Jean-Luc Lamotte, et al.. Selecting Outstanding Patterns Based on Their Neighbourhood. 20th International Symposium on Intelligent Data Analysis, IDA 2022, Apr 2022, Rennes, France. pp.185-198, ⟨10.1007/978-3-031-01333-1_15⟩. ⟨hal-03658500⟩
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