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.
Document type :
Conference papers
Complete list of metadatas

Cited literature [16 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01585614
Contributor : Annabelle Filatre <>
Submitted on : Sunday, September 22, 2019 - 1:11:44 PM
Last modification on : Saturday, October 19, 2019 - 1:13:47 AM

File

Paper_AGILE_2012.pdf
Publisher files allowed on an open archive

Identifiers

  • HAL Id : hal-01585614, version 1

Citation

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, AGILE: Association of Geographic Information Laboratories in Europe, Apr 2012, Avignon, France. pp.197-202. ⟨hal-01585614⟩

Share

Metrics

Record views

527

Files downloads

6