Math Methods and Models of Products Knowledge Management
( Pp. 35-41)

The purpose of this research work is to review the existing literature on methods and solutions to the problem of efficient storage and processing of semi-structured semantic information, including in the field of product knowledge management. At the beginning of the article, the rationale for the relevance of the study is given, then it discusses possible ways to build an ontology of semantic networks, various types of knowledge representation, a stack of possible technologies on which such networks can potentially be implemented. An explanation of the semantics, ways to search for information in such systems, including an overview of the semantic data query languages used, as well as ready-made implementations of knowledge bases, is given. The result of the research work was the creation of an extensive database of analyzed sources, which raises the problem of processing semi-structured heterogeneous data, as well as searching for information on them. In addition, as a result of the study, the most effective solution to the above problem was derived - the construction of an ontology of knowledge, the representation of knowledge within the ontology, semantic networks and their architecture, and implementation. Finally, the author managed to prove a high degree of relevance of further qualitative and in-depth scientific research on the problem considered in the research work.

Trishin A.A., (2022), MATH METHODS AND MODELS OF PRODUCTS KNOWLEDGE MANAGEMENT. Computational Nanotechnology, 4 => 35-41.

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ontology, semantics, semantic network, knowledge base, knowledge management, product knowledge.