Linguistically summarizing and visualizing information from data warehouses
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F20%3A10245519" target="_blank" >RIV/61989100:27510/20:10245519 - isvavai.cz</a>
Result on the web
<a href="https://symopis.sf.bg.ac.rs/download/Zbornik%20SYMOPIS%202020.pdf" target="_blank" >https://symopis.sf.bg.ac.rs/download/Zbornik%20SYMOPIS%202020.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Linguistically summarizing and visualizing information from data warehouses
Original language description
Data visualization is the output of the business intelligence concept for end-users. It is considered as a mean for understanding developments in a company and as a supporting tool for decision-making. A high amount of work is realized in all stages of developing a business intelligence solution, including visualizing information and mined knowledge on dashboards. When dashboards fail to communicate efficiently and effectively it jeopardizes all effort already done. This work discusses augmenting dashboards by the short quantified sentences of natural language. Less statistically literate domain experts and novice professionals might especially benefit from this visualization. Short quantified sentences are understandable despite the professional background. In addition, several data cannot be explained by graphs or in tables. It holds for the non-linear dependencies among attributes and flexible concepts. Finally, this approach is less sensitive to the lower quality and imprecision in data, which especially holds for data extracted from the external sources into the company's data warehouses.
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
10200 - Computer and information sciences
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
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
XLVII International Symposium on Operational Research (SYM-OP-IS 2020) : proceedings : Belgrade, Serbia, September 20-23, 2020
ISBN
978-86-7395-429-5
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
"313 "- 317
Publisher name
Univerzitet u Beogradu
Place of publication
Bělehrad
Event location
Bělehrad
Event date
Sep 20, 2020
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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