Improvement of Searching for Appropriate Textual Information Sources Using Association Rules and FCA
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F21%3A10249576" target="_blank" >RIV/61989100:27240/21:10249576 - isvavai.cz</a>
Result on the web
<a href="https://ebooks.iospress.nl/doi/10.3233/FAIA210487" target="_blank" >https://ebooks.iospress.nl/doi/10.3233/FAIA210487</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3233/FAIA210487" target="_blank" >10.3233/FAIA210487</a>
Alternative languages
Result language
angličtina
Original language name
Improvement of Searching for Appropriate Textual Information Sources Using Association Rules and FCA
Original language description
This paper deals with an optimization of methods for recommending relevant text sources. We summarize methods that are based on a theory of Association Rules and Formal Conceptual Analysis which are computationally demanding. Therefore we are applying the 'Iceberg Concepts', which significantly prune output data space and thus accelerate the whole process of the calculation. Association Rules and the Relevant Ordering, which is an FCA-based method, are applied on data obtained from explications of an atomic concept. Explications are procured from natural language sentences formalized into TIL constructions and processed by a machine learning algorithm. TIL constructions are utilized only as a specification language and they are described in numerous publications, so we do not deal with TIL in this paper. (C) 2021 The authors and IOS Press.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS 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
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Frontiers in Artificial Intelligence and Applications. Volume 343
ISSN
0922-6389
e-ISSN
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Volume of the periodical
343
Issue of the periodical within the volume
343
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
11
Pages from-to
204-214
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85123752950