8 research outputs found

    Learning Multiple Temporal Matching for Time Series Classification

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    12International audienceIn real applications, time series are generally of complex structure, exhibiting different global behaviors within classes. To discriminate such challenging time series, we propose a multiple temporal matching approach that reveals the commonly shared features within classes, and the most differential ones across classes. For this, we rely on a new framework based on the variance/covariance criterion to strengthen or weaken matched observations according to the induced variability within and between classes. The experiments performed on real and synthetic datasets demonstrate the ability of the multiple temporal matching approach to capture fine-grained distinctions between time series

    New temporal matching strategies for time series discrimination

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    International audienceIn real applications it is not rare for time series of the same class to exhibit dissimilarities in their overall behaviors, or that time series from different classes have slightly similar shapes \cite{DouzalPR}. To discriminate between such challenging time series, we present a new approach for training discriminative matching that connects time series with respect to the commonly shared features within classes, and the greatest differential across classes. For this, we rely on a variance/covariance criterion to strengthen or weaken matched observations according to the induced variability within and between classes. In this paper, learned discriminative matching is used to define a locally weighted time series metric, which restricts time series comparison to discriminative features. The relevance of the proposed approach is studied through a nearest neighbor time series classification on simulated and real datasets. The experiments performed demonstrate the ability of learned matching to capture fine-grained distinctions between time series, and outperform the standard approaches, all the more so that time series behaviors within the same class are comple

    À QUELS PRODUITS LE CONSOMMATEUR ASSOCIE-T-IL LA NOTION DE TERROIR : ANALYSE COMPARÉE SELON L'ÂGE ET L'ORIGINE GÉOGRAPHIQUE

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    The purpose of this research is to investigate the evocation of territorial products by people who live in Brittany and Pays de Loire in the West of France. Among the answers, wine and cheese are widely evocated by 1157 persons whilst bread is more evocated than “foie gras” particularly by the youngers. The association between geographical origin of consumers suggests a “folklorisation” sustained by inhabitants.L’article met en évidence une différence dans les produits du terroir qui sont évoqués selon l’appartenance régionale et selon la catégorie générationnelle. L’étude a été menée auprès de 1157 sujets Bretons et Ligériens qui appartiennent d’un côté aux générations X et Y et de l’autre aux générations Baby-boom et Héritage. Les réponses montrent que le vin et le fromage remportent la palme des produits du terroir les plus cités quelles que soient les caractéristiques d’âge et d’origine géographique, il y a des différences sur les autres produits cités. Ainsi, le pain vient détrôner le foie gras chez les générations les plus jeunes. Enfin, l’association entre les produits du terroir cités et l’origine géographique du consommateur suggère une forme de folkorisation des produits alimentaires entretenue par les habitants
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