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Communication dans un congrès

Finding Relevant Sequences With The Least Temporal Contradiction Measure: Application to Hydrological Data

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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Communication dans un congrès
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https://hal.archives-ouvertes.fr/hal-01585614
Déposant : Annabelle Filatre <>
Soumis le : dimanche 22 septembre 2019 - 13:11:44
Dernière modification le : mercredi 30 septembre 2020 - 03:25:44
Archivage à long terme le : : dimanche 9 février 2020 - 03:01:13

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Paper_AGILE_2012.pdf
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  • HAL Id : hal-01585614, version 1
  • IRSTEA : PUB00037843

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Hugo Alatrista Salas, Jérôme Azé, Sandra Bringay, Frédéric Flouvat, Nazha Selmaoui-Folcher, et al.. Finding Relevant Sequences With The Least Temporal Contradiction Measure: Application to Hydrological Data. AGILE: International Conference on Geographic Information Science, Apr 2012, Avignon, France. pp.197-202. ⟨hal-01585614⟩

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