Linguistic Characterization of Natural Data by Applying Intermediate Quantifiers on Fuzzy Association Rules

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F17%3AA1801RAV" target="_blank" >RIV/61988987:17610/17:A1801RAV - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Linguistic Characterization of Natural Data by Applying Intermediate Quantifiers on Fuzzy Association Rules

Popis výsledku v původním jazyce

The objective of this paper is to apply fuzzy natural logic together with the FuzzyGUHA method for analysis and linguistic characterization of scientfic data. FuzzyGUHA is a tool for extracting linguistic association rules from data. Obtained associationsare IF-THEN rules composed of evaluative linguistic expressions, which allowthe quantities to be characterized with vague linguistic terms such as very small,big, medium etc. Originally, fuzzy GUHA provides several numerical indices ofrule quality, which may not be easily understandable for domain experts that are notfamiliar with GUHA association rules. Therefore, we show in this paper that the theoryof intermediate quantfiers (a constituent of fuzzy natural logic) can be applied to theresults in an automatic manner in order to obtain natural linguistic summarization.We also present an idea of how the theory of generalized Aristotles's syllogisms can beused for a detailed data analysis

Název v anglickém jazyce

Linguistic Characterization of Natural Data by Applying Intermediate Quantifiers on Fuzzy Association Rules

Popis výsledku anglicky

The objective of this paper is to apply fuzzy natural logic together with the FuzzyGUHA method for analysis and linguistic characterization of scientfic data. FuzzyGUHA is a tool for extracting linguistic association rules from data. Obtained associationsare IF-THEN rules composed of evaluative linguistic expressions, which allowthe quantities to be characterized with vague linguistic terms such as very small,big, medium etc. Originally, fuzzy GUHA provides several numerical indices ofrule quality, which may not be easily understandable for domain experts that are notfamiliar with GUHA association rules. Therefore, we show in this paper that the theoryof intermediate quantfiers (a constituent of fuzzy natural logic) can be applied to theresults in an automatic manner in order to obtain natural linguistic summarization.We also present an idea of how the theory of generalized Aristotles's syllogisms can beused for a detailed data analysis

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10102 - Applied mathematics

Projekt

<a href="/cs/project/GA16-19170S" target="_blank" >GA16-19170S: Fuzzy parciální logika</a><br>

Návaznosti

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

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Pardubice, Czech Republic September 17-20, 2017 Proceedings of the 20th Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty

ISBN

978-80-7464-932-5

ISSN

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e-ISSN

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Počet stran výsledku

12

Strana od-do

115-126

Název nakladatele

University of Ostrava

Místo vydání

University of Ostrava

Místo konání akce

Pardubice

Datum konání akce

17. 9. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000418391500014