Mathematical morphology tools to evaluate periodic linguistic summaries

Gilles Moyse (1) , Marie-Jeanne Lesot (1) , Bernadette Bouchon-Meunier (1)

1 LFI - Learning, Fuzzy and Intelligent systems

This paper considers the task of establishing periodic linguis- tic summaries of the form "Regularly, the data take high values", enriched with an estimation of the period and a linguistic formulation. Within the framework of methods that address this task testing whether the dataset contains regularly spaced groups of high and low values with approx- imately constant size, it proposes a mathematical morphology (MM) approach based on watershed. It compares the proposed approach to other MM methods in an experimental study based on artificial data with different forms and noise types.

Mots clés: Fuzzy linguistic summaries; Periodicity computing; Mathematical Morphology; Temporal data mining; Watershed

Domaines: Algorithme et structure de données [cs.DS]; Mathématique discrète [cs.DM]; Recherche d'information [cs.IR]; Apprentissage [cs.LG]

Gilles Moyse, Marie-Jeanne Lesot, Bernadette Bouchon-Meunier. Mathematical morphology tools to evaluate periodic linguistic summaries. Flexible Query Answering Systems, Sep 2013, Granada, Spain. pp.257-268, ⟨10.1007/978-3-642-40769-7_23⟩. ⟨hal-00932844⟩