id: 05796694
dt: a
an: 05796694
au: Lelu, Alain; Cadot, Martine
ti: Statistically valid links and anti-links between words and between
    documents: applying Tournebool randomization test to a Reuters
    collection.
so: Guillet, F. (ed.) et al., Advances in knowledge discovery and management.
    Selected papers based on the presentations at the “Extraction et
    gestion des connaissances" conference 2009 (EGC), Strasbourg, France,
    January 2009. Berlin: Springer (ISBN 978-3-642-00579-4/hbk). Studies in
    Computational Intelligence 292, 307-324 (2010).
py: 2010
pu: Berlin: Springer
la: EN
cc: 
ut: statistical graph extraction; randomization test; robust data mining;
    unsupervised learning; text mining
ci: 
li: doi:10.1007/978-3-642-00580-0_18
ab: Summary: Neighborhood is a central concept in data mining, and a bunch of
    definitions have been implemented, mainly rooted in geometrical or
    topological considerations. We propose here a statistical definition of
    neighborhood: our TourneBool randomization test processes an objects
    $\times$ attributes binary table in order to establish which
    inter-attribute relations are fortuitous, and which ones are
    meaningful, without requiring any pre-defined statistical model, while
    taking into account the empirical distributions. It ensues a robust and
    statistically validated graph. We present a full-scale experiment on
    one of the public access Reuters test corpus. We characterize the
    resulting word graph by a series of indicators, such as clustering
    coefficients, degree distribution and correlation, cluster modularity
    and size distribution. Another graph structure stems from this process:
    the one conveying the negative “counter-relations” between words,
    i.e. words which “steer clear” one from another. We characterize in
    the same way the counter-relation graph. At last we generate the couple
    of valid document graphs (i.e. links and anti-links) and evaluate them
    by taking into account the Reuters document categories.
rv: