Application of boolean valued and fuzzy model theory for knowledge base development

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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.

Original languageEnglish
Title of host publicationSIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages868-871
Number of pages4
ISBN (Electronic)9781728144016
DOIs
Publication statusPublished - Oct 2019
Event2019 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2019 - Novosibirsk, Russian Federation
Duration: 21 Oct 201927 Oct 2019

Publication series

NameSIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings

Conference

Conference2019 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2019
CountryRussian Federation
CityNovosibirsk
Period21.10.201927.10.2019

Keywords

  • Fuzzification
  • Fuzzy Model
  • Knowledge Base
  • Knowledge Representation Boolean-valued Model
  • Precedent
  • Precedent Model

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