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Knowledge Transformation via Different Structures of Concepts and its Application in Argumentation Theory and Case-Based Reasoning Full article

Conference International Symposium on Knowledge, Ontology, and Theory
04-04 Dec 2021 , Новосибирск, Россия
Source International Symposium on Knowledge, Ontology, and Theory (KNOTH)
Compilation, 2021. 114 c.
Output data Year: 2021, Pages: 20-25 Pages count : 6 DOI: 10.1109/KNOTH54462.2021.9685027
Tags Argumentation; Case-Based Reasoning; FCA; Fragment of Atomic Diagram; Knowledge Representation; Knowledge Transformation; Model Theory of Subject Domains
Authors Palchunov D. 1
Affiliations
1 Laboratory of Computability Theory, Applied Logic Sobolev Institute of Mathematics, Novosibirsk, Russian Federation

Abstract: The article is devoted to solving some problems of argumentation theory and case-based reasoning. For this purpose, we develop methods for transforming knowledge presented in various structures of concepts. The correspondence rules between concepts of different levels of generality are investigated. We use formal concept lattices to assess knowledge and test the equivalence of knowledge transformations. Based on Melchuk's theory 'Meaning <=> text', formal methods of extracting knowledge from natural language texts and representing the extracted knowledge are proposed. To formally represent domain case structures, we modify the predicates by adding special situation-constants to them. The concept of ontological homomorphism of algebraic systems is introduced, on the basis of which the similarity of cases is defined. These constructions are used to develop argumentation structures that use case-based reasoning. © 2021 IEEE.
Cite: Palchunov D.
Knowledge Transformation via Different Structures of Concepts and its Application in Argumentation Theory and Case-Based Reasoning
In compilation International Symposium on Knowledge, Ontology, and Theory (KNOTH). 2021. – C.20-25. DOI: 10.1109/KNOTH54462.2021.9685027 Scopus OpenAlex
Identifiers:
Scopus: 2-s2.0-85126801068
OpenAlex: W4210579054
Citing: Пока нет цитирований
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