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
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DOI - Digital Object Identifier
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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
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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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