Linguistic Representation by Fuzzy Formal Concept and Interval Type-2 Feature Selection

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F17%3A10238750" target="_blank" >RIV/61989100:27240/17:10238750 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27740/17:10238750

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007%2F978-3-319-53480-0_105" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-319-53480-0_105</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-53480-0_105" target="_blank" >10.1007/978-3-319-53480-0_105</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Linguistic Representation by Fuzzy Formal Concept and Interval Type-2 Feature Selection

Popis výsledku v původním jazyce

Natural language is always seen as a source of uncertainty and vagueness. Fuzzy logic (FL) is a powerful tool for representing and treating perceptions which are the inputs and outputs of a linguistic model. In fact, a linguistic representation is a methodology that moves from crisp measures to uncertain words or fuzzy concepts. This theory uses fuzzy sets to encode and represent linguistic concepts. In this paper, an interval type-2 fuzzy formal concept IT-2FFC is presented as a new approach for extracting knowledge in a linguistic model. The method represents a combination of two techniques: fuzzy formal concept (FFC) for visualizing data and interval type-2 fuzzy sets (IT-2FSs) for feature selection. The obtained results demonstrate that the method applied can help human to make subjective judgments and make decision in a knowledge model.

Název v anglickém jazyce

Linguistic Representation by Fuzzy Formal Concept and Interval Type-2 Feature Selection

Popis výsledku anglicky

Natural language is always seen as a source of uncertainty and vagueness. Fuzzy logic (FL) is a powerful tool for representing and treating perceptions which are the inputs and outputs of a linguistic model. In fact, a linguistic representation is a methodology that moves from crisp measures to uncertain words or fuzzy concepts. This theory uses fuzzy sets to encode and represent linguistic concepts. In this paper, an interval type-2 fuzzy formal concept IT-2FFC is presented as a new approach for extracting knowledge in a linguistic model. The method represents a combination of two techniques: fuzzy formal concept (FFC) for visualizing data and interval type-2 fuzzy sets (IT-2FSs) for feature selection. The obtained results demonstrate that the method applied can help human to make subjective judgments and make decision in a knowledge model.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název statě ve sborníku

Advances in Intelligent Systems and Computing. Volume 557

ISBN

978-3-319-53479-4

ISSN

2194-5357

e-ISSN

neuvedeno

Počet stran výsledku

11

Strana od-do

1071-1081

Název nakladatele

Springer

Místo vydání

Berlin

Místo konání akce

Porto

Datum konání akce

16. 12. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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