{"title":"From Texts to Knowledge Graph in the Semantic Library LibMeta","authors":"O. M. Ataeva, V. A. Serebryakov, N. P. Tuchkova","doi":"10.1134/s1995080224602625","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The problem of constructing a knowledge graph for previously unprocessed scientific texts is studied. The task is to analyze the use of various machine processing methods for extracting text semantics using the example of an interdisciplinary subject area. The goal of the research is to create a semantic model of the subject area of an interdisciplinary scientific journal and use a knowledge graph to navigate through data. The semantic model is based on the ontology of the LibMeta library. Texts and metadata receive connections due to the processing procedure and become part of the ontology of the semantic library. The interdisciplinary subject area is integrated into the library content as a related area of the ‘‘mathematics’’ ontology of the LibMeta library. A comparison of texts is carried out according to different characteristics, thematic proximity, commonality of research methods and approaches, problem setting and their symbolic representation. The results of preliminary text processing and the results in the form of a knowledge graph integrated into the library content are presented. The formulation of the problem of constructing an ontology and a knowledge graph for an interdisciplinary subject area adjacent to mathematics is considered by the authors as part of the general problem of managing mathematical knowledge.</p>","PeriodicalId":46135,"journal":{"name":"Lobachevskii Journal of Mathematics","volume":null,"pages":null},"PeriodicalIF":0.8000,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Lobachevskii Journal of Mathematics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1134/s1995080224602625","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS","Score":null,"Total":0}
引用次数: 0
Abstract
The problem of constructing a knowledge graph for previously unprocessed scientific texts is studied. The task is to analyze the use of various machine processing methods for extracting text semantics using the example of an interdisciplinary subject area. The goal of the research is to create a semantic model of the subject area of an interdisciplinary scientific journal and use a knowledge graph to navigate through data. The semantic model is based on the ontology of the LibMeta library. Texts and metadata receive connections due to the processing procedure and become part of the ontology of the semantic library. The interdisciplinary subject area is integrated into the library content as a related area of the ‘‘mathematics’’ ontology of the LibMeta library. A comparison of texts is carried out according to different characteristics, thematic proximity, commonality of research methods and approaches, problem setting and their symbolic representation. The results of preliminary text processing and the results in the form of a knowledge graph integrated into the library content are presented. The formulation of the problem of constructing an ontology and a knowledge graph for an interdisciplinary subject area adjacent to mathematics is considered by the authors as part of the general problem of managing mathematical knowledge.
期刊介绍:
Lobachevskii Journal of Mathematics is an international peer reviewed journal published in collaboration with the Russian Academy of Sciences and Kazan Federal University. The journal covers mathematical topics associated with the name of famous Russian mathematician Nikolai Lobachevsky (Lobachevskii). The journal publishes research articles on geometry and topology, algebra, complex analysis, functional analysis, differential equations and mathematical physics, probability theory and stochastic processes, computational mathematics, mathematical modeling, numerical methods and program complexes, computer science, optimal control, and theory of algorithms as well as applied mathematics. The journal welcomes manuscripts from all countries in the English language.