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Extraction de motifs spatio-temporels à différentes échelles avec gestion de relations spatiales qualitatives

Abstract : Georeferenced databases contain a huge volume of temporal and spatial data. They are notably used in environmental analysis. Several works address the problem of mining those data, but none are able to take into account the richness of the data and especially their spatial and temporal dimensions. In this paper, we focus on the extraction of a new kind of spatiotemporal patterns which consider the relationship between spatial objects and also various geographical scales. We propose an algorithm, STR_PrefixGrowth, which can be applied on a huge amont of data. The proposed method is evaluated on hydrological data collected on the Saône basin during the last 19 years. Our experiments emphasize the contribution of our approach toward the existing methods.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00735616
Contributor : Maguelonne Teisseire <>
Submitted on : Wednesday, September 26, 2012 - 11:41:28 AM
Last modification on : Wednesday, October 7, 2020 - 10:04:09 AM
Long-term archiving on: : Friday, December 16, 2016 - 5:13:47 PM

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  • HAL Id : lirmm-00735616, version 1
  • IRSTEA : PUB00054267

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Mickaël Fabrègue, Agnès Braud, Sandra Bringay, Florence Le Ber, Maguelonne Teisseire. Extraction de motifs spatio-temporels à différentes échelles avec gestion de relations spatiales qualitatives. Inforsid, May 2012, Montpellier, France. pp.123-138. ⟨lirmm-00735616⟩

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