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Pruning in Map-Reduce Style CbO Algorithms

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F20%3A73601615" target="_blank" >RIV/61989592:15310/20:73601615 - isvavai.cz</a>

  • Result on the web

    <a href="https://link.springer.com/chapter/10.1007%2F978-3-030-57855-8_8" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-030-57855-8_8</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-030-57855-8_8" target="_blank" >10.1007/978-3-030-57855-8_8</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Pruning in Map-Reduce Style CbO Algorithms

  • Original language description

    Enumeration of formal concepts is crucial in formal concept analysis. Particularly efficient for this task are algorithms from the Close-by-One family (shortly, CbO-based algorithms). State-of-the-art CbO-based algorithms, e.g. FCbO, In-Close4, and In-Close5, employ several techniques, which we call pruning, to avoid some unnecessary computations. However, the number of the formal concepts can be exponential w.r.t. dimension of the input data. Therefore, the algorithms do not scale well and large datasets become intractable. To resolve this weakness, several parallel and distributed algorithms were proposed. We propose new CbO-based algorithms intended for Apache Spark or a similar programming model and show how the pruning can be incorporated into them. We experimentally evaluate the impact of the pruning and demonstrate the scalability of the new algorithm.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Ontologies and Concepts in Mind and Machine

  • ISBN

    978-3-030-57854-1

  • ISSN

    0302-9743

  • e-ISSN

  • Number of pages

    12

  • Pages from-to

    103-116

  • Publisher name

    Springer

  • Place of publication

    Cham

  • Event location

    Bolzano; Italia

  • Event date

    Sep 18, 2020

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article