Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
Application of boolean valued and fuzzy model theory for knowledge base development. / Yakhyaeva, Gulnara.
SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. стр. 868-871 8958245 (SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
}
TY - GEN
T1 - Application of boolean valued and fuzzy model theory for knowledge base development
AU - Yakhyaeva, Gulnara
N1 - Publisher Copyright: © 2019 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2019/10
Y1 - 2019/10
N2 - In paper we propose a semantic model for representing knowledge. This approach is based on the theory of fuzzy models, which is a conservative extension of the classical model theory. In the framework of the proposed approach, first the knowledge extracted from texts of natural language is presented in the form of algebraic systems (precedents of a object domain). Then all precedents are integrated to one Knowledge Base. The knowledge base of the object domain is formalized in the form of two algebraic systems: A Boolean-valued Model and a Fuzzy Model. The Boolean-valued model formalizes semantic (qualitative) knowledge about the object domain. The fuzzy model is intended to formalize statistical (quantitative) knowledge. The proposed methodology is illustrated by the example of the object domain of computer security.
AB - In paper we propose a semantic model for representing knowledge. This approach is based on the theory of fuzzy models, which is a conservative extension of the classical model theory. In the framework of the proposed approach, first the knowledge extracted from texts of natural language is presented in the form of algebraic systems (precedents of a object domain). Then all precedents are integrated to one Knowledge Base. The knowledge base of the object domain is formalized in the form of two algebraic systems: A Boolean-valued Model and a Fuzzy Model. The Boolean-valued model formalizes semantic (qualitative) knowledge about the object domain. The fuzzy model is intended to formalize statistical (quantitative) knowledge. The proposed methodology is illustrated by the example of the object domain of computer security.
KW - Fuzzification
KW - Fuzzy Model
KW - Knowledge Base
KW - Knowledge Representation Boolean-valued Model
KW - Precedent
KW - Precedent Model
UR - http://www.scopus.com/inward/record.url?scp=85079046609&partnerID=8YFLogxK
UR - https://elibrary.ru/item.asp?id=43253212
U2 - 10.1109/SIBIRCON48586.2019.8958245
DO - 10.1109/SIBIRCON48586.2019.8958245
M3 - Conference contribution
AN - SCOPUS:85079046609
T3 - SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings
SP - 868
EP - 871
BT - SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2019
Y2 - 21 October 2019 through 27 October 2019
ER -
ID: 27548131