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Evaluating Association Rules in Boolean Matrix Factorization

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F16%3A33160927" target="_blank" >RIV/61989592:15310/16:33160927 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Evaluating Association Rules in Boolean Matrix Factorization

  • Original language description

    Association rules, or association rule mining, is a well-established and popular method of data mining and machine learning successfully applied in many different areas since mid-nineties. Association rules form a ground of the Asso algorithm for discovery of the first (presumably most important) factors in Boolean matrix factorization. In Asso, the confidence parameter of association rules heavily influences the quality of factorization. However, association rules, in a more general form, appear already in GUHA, a knowledge discovery method developed since mid-sixties. In the paper, we evaluate the use of various (other) types of association rules from GUHA in Asso and, from the other side, a possible utilization of (particular) association rules in other Boolean matrix factorization algorithms not based on the rules. We compare the quality of factorization produced by the modified algorithms with those produced by the original algorithms.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GA15-17899S" target="_blank" >GA15-17899S: Decompositions of Matrices with Boolean and Ordinal Data: Theory and Algorithms</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2016

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proceedings of the 16th ITAT Conference Information Technologies - Applications and Theory, ITAT 2016, Workshop on Computational Intelligence and Data Mining, WCIDM 2016

  • ISBN

    978-1-5370-1674-0

  • ISSN

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

    147-154

  • Publisher name

    CreateSpace Independent Publishing Platform

  • Place of publication

    Bratislava

  • Event location

    Tatranské Matliare

  • Event date

    Sep 15, 2016

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article