Standard

Prototypes of the “natural” concepts discovery. / Vityaev, Evgenii; Pak, Bayar.

в: Cognitive Systems Research, Том 67, 06.2021, стр. 1-8.

Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование

Harvard

Vityaev, E & Pak, B 2021, 'Prototypes of the “natural” concepts discovery', Cognitive Systems Research, Том. 67, стр. 1-8. https://doi.org/10.1016/j.cogsys.2020.12.005

APA

Vityaev, E., & Pak, B. (2021). Prototypes of the “natural” concepts discovery. Cognitive Systems Research, 67, 1-8. https://doi.org/10.1016/j.cogsys.2020.12.005

Vancouver

Vityaev E, Pak B. Prototypes of the “natural” concepts discovery. Cognitive Systems Research. 2021 июнь;67:1-8. doi: 10.1016/j.cogsys.2020.12.005

Author

Vityaev, Evgenii ; Pak, Bayar. / Prototypes of the “natural” concepts discovery. в: Cognitive Systems Research. 2021 ; Том 67. стр. 1-8.

BibTeX

@article{cfd12e2a57a04600860ebc8be40da205,
title = "Prototypes of the “natural” concepts discovery",
abstract = "In works of Eleanor Rosch “natural” concepts was introduced that reflect a high correlated structure of features of objects of the external world. Prototypes of the “natural” concepts are clearest cases of objects that reflect this highly correlated structure. The same high correlated structure manifested in the “natural” phenotypical classification. To formalize this highly correlated structure, we define a special type of probabilistic causal relations and then probabilistic formal concepts as a cyclically connected probabilistic causal relations. Based on these definitions, we developed a method of prototypes discovery and illustrate it on the example of digits{\textquoteright} prototypes discovery.",
keywords = "Clustering, Concepts, Concepts discovery, Data mining, Formal concepts analysis",
author = "Evgenii Vityaev and Bayar Pak",
note = "Funding Information: This work is supported by the Russian Foundation for Basic Research #19-01-00331-a. The study also was carried out within the framework of the state contract of the Sobolev Institute of Mathematics (project no. 0314-2019-0002) regarding the results of the Sections 5–7 . Publisher Copyright: {\textcopyright} 2020 Elsevier B.V. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",
year = "2021",
month = jun,
doi = "10.1016/j.cogsys.2020.12.005",
language = "English",
volume = "67",
pages = "1--8",
journal = "Cognitive Systems Research",
issn = "1389-0417",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Prototypes of the “natural” concepts discovery

AU - Vityaev, Evgenii

AU - Pak, Bayar

N1 - Funding Information: This work is supported by the Russian Foundation for Basic Research #19-01-00331-a. The study also was carried out within the framework of the state contract of the Sobolev Institute of Mathematics (project no. 0314-2019-0002) regarding the results of the Sections 5–7 . Publisher Copyright: © 2020 Elsevier B.V. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2021/6

Y1 - 2021/6

N2 - In works of Eleanor Rosch “natural” concepts was introduced that reflect a high correlated structure of features of objects of the external world. Prototypes of the “natural” concepts are clearest cases of objects that reflect this highly correlated structure. The same high correlated structure manifested in the “natural” phenotypical classification. To formalize this highly correlated structure, we define a special type of probabilistic causal relations and then probabilistic formal concepts as a cyclically connected probabilistic causal relations. Based on these definitions, we developed a method of prototypes discovery and illustrate it on the example of digits’ prototypes discovery.

AB - In works of Eleanor Rosch “natural” concepts was introduced that reflect a high correlated structure of features of objects of the external world. Prototypes of the “natural” concepts are clearest cases of objects that reflect this highly correlated structure. The same high correlated structure manifested in the “natural” phenotypical classification. To formalize this highly correlated structure, we define a special type of probabilistic causal relations and then probabilistic formal concepts as a cyclically connected probabilistic causal relations. Based on these definitions, we developed a method of prototypes discovery and illustrate it on the example of digits’ prototypes discovery.

KW - Clustering

KW - Concepts

KW - Concepts discovery

KW - Data mining

KW - Formal concepts analysis

UR - http://www.scopus.com/inward/record.url?scp=85099035995&partnerID=8YFLogxK

U2 - 10.1016/j.cogsys.2020.12.005

DO - 10.1016/j.cogsys.2020.12.005

M3 - Article

AN - SCOPUS:85099035995

VL - 67

SP - 1

EP - 8

JO - Cognitive Systems Research

JF - Cognitive Systems Research

SN - 1389-0417

ER -

ID: 27415754