DEvIANT: discovering significant exceptional (dis-)agreement within groups

Adnene Belfodil, Wouter Duivesteijn, Marc Plantevit, Sylvie Cazalens, Philippe Lamarre

    Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

    Samenvatting

    We strive to find contexts (i.e., subgroups of entities) under which exceptional (dis-)agreement occurs among a group of individuals, in any type of data featuring individuals (e.g., parliamentarians, customers) performing observable actions (e.g., votes, ratings) on entities (e.g., legislative procedures, movies). To this end, we introduce the problem of discovering statistically significant exceptional contextual intra-group agreement patterns. To handle the sparsity inherent to voting and rating data, we use Krippendorff’s Alpha measure for assessing the agreement among individuals. We devise a branch-and-bound algorithm, named DEvIANT, to discover such patterns. DEvIANT exploits both closure operators and tight optimistic estimates. We derive analytic approximations for the confidence intervals (CIs) associated with patterns for a computationally efficient significance assessment. We prove that these approximate CIs are nested along specialization of patterns. This allows to incorporate pruning properties in DEvIANT to quickly discard non-significant patterns. Empirical study on several datasets demonstrates the efficiency and the usefulness of DEvIANT.

    Originele taal-2Engels
    TitelMachine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Proceedings
    SubtitelEuropean Conference, ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, Proceedings, Part I
    RedacteurenUlf Brefeld, Elisa Fromont, Andreas Hotho, Arno Knobbe, Marloes Maathuis, Céline Robardet
    Plaats van productieCham
    UitgeverijSpringer Nature
    Pagina's3-20
    Aantal pagina's18
    ISBN van elektronische versie978-3-030-46150-8
    ISBN van geprinte versie978-3-030-46149-2
    DOI's
    StatusGepubliceerd - 2020
    Evenement2019 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2019) - Wurzburg, Duitsland
    Duur: 16 sep 201920 sep 2019
    Congresnummer: 19
    http://ecmlpkdd2019.org/

    Publicatie series

    NaamLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume11906 LNAI
    ISSN van geprinte versie0302-9743
    ISSN van elektronische versie1611-3349

    Congres

    Congres2019 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2019)
    Verkorte titelECML PKDD 2019
    LandDuitsland
    StadWurzburg
    Periode16/09/1920/09/19
    Internet adres

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