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On the determination of query execution patterns of the application of the Anchor Data modeling method using machine-learning methods

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F17%3A10236174" target="_blank" >RIV/61989100:27510/17:10236174 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    On the determination of query execution patterns of the application of the Anchor Data modeling method using machine-learning methods

  • Original language description

    The Anchor Data Modeling (ADM) is a relational data modeling method that supports the phenomenon of agile data modeling in which evolutionary aspects of data management are addressed. In this paper, we focus on the determination of possible patterns that could help to understand potential benefits for the query execution performance, when a database schema is implemented using the ADM method. Patterns should imply specific query structure that may be linked to positive impacts on the querying performance, if a data mart is designed using the ADM method.

  • 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

    <a href="/en/project/GA16-01298S" target="_blank" >GA16-01298S: Dynamic Decision-making of a Steel Producer under Emission Control</a><br>

  • Continuities

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

Others

  • Publication year

    2017

  • 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 12th International Conference on Strategic Management and its Support by Information Systems: May 25th-26th, 2017, Ostrava, Czech Republic

  • ISBN

    978-80-248-4046-8

  • ISSN

    2570-5776

  • e-ISSN

    neuvedeno

  • Number of pages

    11

  • Pages from-to

    434-444

  • Publisher name

    VŠB - Technical University of Ostrava

  • Place of publication

    Ostrava

  • Event location

    Ostrava

  • Event date

    May 25, 2017

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000417344100049