Study of Thematic and Terminological Transformation of Collections of Scientific Articles in Interdisciplinary Fields of Knowledge

• Published in: Automatic documentation and mathematical linguistics Vol. 58; no. 6; pp. 420 - 430
• Main Authors: Fedorets, O. V., Soloshenko, N. S.
• Format: Journal Article
• Language: English
• Published: Moscow Pleiades Publishing 01.12.2024; Springer Nature B.V
• Subjects: Artificial intelligence; Computer Science; Information Analysis; Information Storage and Retrieval; Machine learning; Robotics; SRSTI; thematic collections of articles; articles in scientific journals; terminological analysis; scientometrics; thematic profiles of collections; TF-IDF; descriptive sets; VINITI RAS database; information search; similarity coefficient
• ISSN: 0005-1055; 1934-8371
• DOI: 10.3103/S0005105524700390

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.”