Fuzzy functional dependencies and linguistic interpretations employed in knowledge discovery tasks from relational databases
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F20%3A10244402" target="_blank" >RIV/61989100:27510/20:10244402 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0952197619303136" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0952197619303136</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.engappai.2019.103395" target="_blank" >10.1016/j.engappai.2019.103395</a>
Alternative languages
Result language
angličtina
Original language name
Fuzzy functional dependencies and linguistic interpretations employed in knowledge discovery tasks from relational databases
Original language description
Knowledge discovery from databases copes with several problems including the heterogeneity of data and interpreting the solution in an understandable and convenient form for domain experts. Fuzzy logic approaches based on the computing with words paradigm are very appealing since they offer the possibility to express useful knowledge from a large volume of data by linguistic terms, which are easily understandable for diverse users. In this paper, the novel descriptive data mining algorithm based on fuzzy functional dependencies has been proposed. In the first step, data are fuzzified, which ensures the same manipulation of crisp and fuzzy data. The data mining step is based on revealing fuzzy functional dependencies among considered attributes. In the final step, the mined knowledge is interpreted linguistically by the fuzzy modifiers and quantifiers. The proposed algorithm has been explained on illustrative data and tested on real-world dataset. Finally, its benefits, weak points and possible future research topics are discussed.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
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
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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
Name of the periodical
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
ISSN
0952-1976
e-ISSN
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Volume of the periodical
88
Issue of the periodical within the volume
February 2020
Country of publishing house
GB - UNITED KINGDOM
Number of pages
15
Pages from-to
103395
UT code for WoS article
000510523600019
EID of the result in the Scopus database
2-s2.0-85075551235