{"title":"Study of Thematic and Terminological Transformation of Collections of Scientific Articles in Interdisciplinary Fields of Knowledge","authors":"O. V. Fedorets, N. S. Soloshenko","doi":"10.3103/S0005105524700390","DOIUrl":null,"url":null,"abstract":"<p>This paper presents the methodology of the quantitative study of the dynamics of changes in the thematic structure of collections and vocabulary of terms that were aimed at selecting documents into thematic collections, creating thematic (classification and subject) profiles of these collections in different chronological periods and a comparative analysis of these profiles. The profiles are treated as descriptive sets, with TF-IDF used as the keyword weight. The methodology is tested in two collections, “Robotics and Robotic Systems” and “Intelligent Systems, Artificial Intelligence, and Machine Learning.”</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"58 6","pages":"420 - 430"},"PeriodicalIF":0.5000,"publicationDate":"2025-02-17","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/S0005105524700390","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
This paper presents the methodology of the quantitative study of the dynamics of changes in the thematic structure of collections and vocabulary of terms that were aimed at selecting documents into thematic collections, creating thematic (classification and subject) profiles of these collections in different chronological periods and a comparative analysis of these profiles. The profiles are treated as descriptive sets, with TF-IDF used as the keyword weight. The methodology is tested in two collections, “Robotics and Robotic Systems” and “Intelligent Systems, Artificial Intelligence, and Machine Learning.”
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.