{"title":"Correspondence between Hierarchical Knowledge Classifiers","authors":"P. A. Kalachikhin","doi":"10.3103/S0005105524010084","DOIUrl":null,"url":null,"abstract":"<p>Hierarchical, descriptive, and faceted methods of constructing knowledge classifiers and also the classification of knowledge using folksnomies are described. Mathematical models to formalize the listed methods of constructing classifiers are presented. A general description of the classifiers of the Russian Science Citation Index, Code of State Categories Scientific and Technical Information, and Universal Decimal Classification is given. The Chinese experience of classifying scientific publications and the American experience of classifying patent documents are analyzed. An alternative possibility for classifying scientific publications using clustering with bibliometric indicators and using keywords is indicated. A review of the main methods and means of comparing knowledge classifiers using qualifiers and expert competencies is carried out. A new approach to the compilation of knowledge classifiers based on their reduction to oriented trees and the construction of homomorphisms between these graphs is proposed.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.3103/S0005105524010084","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Hierarchical, descriptive, and faceted methods of constructing knowledge classifiers and also the classification of knowledge using folksnomies are described. Mathematical models to formalize the listed methods of constructing classifiers are presented. A general description of the classifiers of the Russian Science Citation Index, Code of State Categories Scientific and Technical Information, and Universal Decimal Classification is given. The Chinese experience of classifying scientific publications and the American experience of classifying patent documents are analyzed. An alternative possibility for classifying scientific publications using clustering with bibliometric indicators and using keywords is indicated. A review of the main methods and means of comparing knowledge classifiers using qualifiers and expert competencies is carried out. A new approach to the compilation of knowledge classifiers based on their reduction to oriented trees and the construction of homomorphisms between these graphs is proposed.
期刊介绍:
Automatic Documentation and Mathematical Linguistics is an international peer reviewed journal that covers all aspects of automation of information processes and systems, as well as algorithms and methods for automatic language analysis. Emphasis is on the practical applications of new technologies and techniques for information analysis and processing.