@inproceedings{e3d73b92485f4186b0bb24030db1c7be,
title = "Application of boolean valued and fuzzy model theory for knowledge base development",
abstract = "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.",
keywords = "Fuzzification, Fuzzy Model, Knowledge Base, Knowledge Representation Boolean-valued Model, Precedent, Precedent Model",
author = "Gulnara Yakhyaeva",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 2019 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2019 ; Conference date: 21-10-2019 Through 27-10-2019",
year = "2019",
month = oct,
doi = "10.1109/SIBIRCON48586.2019.8958245",
language = "English",
series = "SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "868--871",
booktitle = "SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings",
address = "United States",
}