Formalization of Digital Knowledge And Modern Approaches to Data Management
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Ключевые слова

Digital knowledge
Formalization of knowledge
Digital management
knowledge management system

Как цитировать

Arevadze, K. (2024). Formalization of Digital Knowledge And Modern Approaches to Data Management. Georgian Scientists, 6(1), 26–32. https://doi.org/10.52340/gs.2024.06.01.05

Аннотация

Effective management approaches involve the utilization of formalized knowledge acquired within the organization and subsequently the deployment of decision support systems to facilitate decision-making. For the formalization of knowledge accumulated within organizations, it is necessary to explore the forms of formalization of data. To effectively develop good knowledge bases, a good knowledge representative is needed. Let's discuss the aspects of knowledge representation in the context of semantic web using as an example. However, it is possible to add or maintain a lot of complex data. There are some common views of date storage. Document System, Database oriented a subject, Relational database, Object relational database. Choosing a programming language for a knowledge management system involves considering additional components, such as: Flexibility, Simplicity, Efficiency, Expansion, Support, Portability, Reliability.

Various types of knowledge representation logics are utilized, including: Propositional Logic (PL), First-Order Logic (FOL), Higher-Order Logic (HOL), Modal Logic, Fuzzy Logic, Multivalued Logic, Temporal Logic, Description Logics (DL), Frame, Rule-Based Systems.

Regardless of the type of organization, the system of using tools simplifies the formalization and representation of its knowledge, which forms the basis for fast and efficient management.

https://doi.org/10.52340/gs.2024.06.01.05
PDF (English)

Библиографические ссылки

Tamar Bitchikashvili, Liliy Petriashvili, and Luka Kavtelishvili Jang. 2023. “DIGITALIZATION OF MANAGEMENT OF A HIGHER EDUCATIONAL INSTITUTION, NATIONAL AND INTERNATIONAL CHALLENGES AND WAYS OF SOLUTION”. World Science, no. 3(81) (September). https://doi.org/10.31435/rsglobal_ws/30092023/8032

Doborjginidze G., Petriashvili L. (2020) “Improving Efficiency of Inventory Identification System” European Science Review, Issue 1-2. DOI: https://doi.org/10.29013/ESR-20-1.2-84-88 Pages: 84 – 88

Giorgi Doborjginidze, Lily Petriashvili, Mariam Inaishvili (2021) Optimization of Inventory Management in the Supply Chain. Journal of Communication and Computer, David Publishing Company 16 (2021) 1-5 DOI: https://doi.org/10.17265/1548-7709/2021.01.001

Giorgi Doborjginidze, Lily Petriashvili, & Mariam Inaishvili. (2020). IMPROVE EFFICIENCY AND RELIABILITY OF SUPPLY CHAINS USING SMART CONTRACTS. International Academy Journal Web of Scholar, (8(50), 1-6. https://doi.org/10.31435/rsglobal_wos/30122020/7261

Nona Otkhozoria, Lily Petriashvili, Ani Kudukhashvili, and Nino Kakhurashvili. 2023. “COMPARATIVE ANALYSIS OF COMPLEX INFORMATION SYSTEM TESTING METHODS”. World Science, no. 4(82) (November). https://doi.org/10.31435/rsglobal_ws/30122023/8076

Propositional Logic (PL): Represents knowledge using simple propositions and logical connectives.

First-Order Logic (FOL): Allows the representation of complex relationships using variables, quantifiers, and predicates.

Higher-Order Logic (HOL): Extends first-order logic by allowing quantification over functions and predicates.

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