The Least Temporal Contradiction Measure: Application to Hydrological Data

Hugo Alatrista Salas 1 Jérôme Azé 2, 3 Sandra Bringay 4 Flavie Cernesson 1 Frédéric Flouvat 5 Nazha Selmaoui-Folcher 5 Maguelonne Teisseire 1, 4
3 AMIB - Algorithms and Models for Integrative Biology
LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau], LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France
4 TATOO - Fouille de données environnementales
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : In this paper, we present a knowledge discovery process applied to hydrological data. To achieve this objective, we apply an algorithm to extract sequential patterns on data collected at stations located along several rivers. The data is pre-processed in order to obtain different spatial proximities and the number of patterns is estimated to highlight the influence of defined spatial relationship. We provide an objective measure of assessment, called the least temporal contradiction, to help the expert in discovering new knowledge. Such elements can be used to assess spatialized indicators to assist the interpretation of ecological and rivers monitoring pressure data.
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Contributor : Hugo Alatrista Salas <>
Submitted on : Tuesday, March 19, 2013 - 10:20:31 AM
Last modification on : Friday, March 29, 2019 - 9:12:06 AM


  • HAL Id : lirmm-00802112, version 1


Hugo Alatrista Salas, Jérôme Azé, Sandra Bringay, Flavie Cernesson, Frédéric Flouvat, et al.. The Least Temporal Contradiction Measure: Application to Hydrological Data. AGILE: International Conference on Geographic Information Science, 2012, Avignon, France. pp.197-202. ⟨lirmm-00802112⟩



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