Analysis of the terminological structure of control theory
- Authors: Novikov D.A.1, Gubanov D.A.1
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Affiliations:
- V.A. Trapeznikov Institute of Control Sciences of RAS
- Issue: No 110 (2024)
- Pages: 181-210
- Section: Networking in control sciences
- URL: https://journals.rcsi.science/1819-2440/article/view/285152
- DOI: https://doi.org/10.25728/ubs.2024.110.7
- ID: 285152
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Abstract
A glossary of fundamental concepts is crucial for standardizing terminology, supporting education, and fostering interdisciplinary research, enhancing mutual understanding and effective communication in the field. In control theory, experts from the Institute of Control Sciences of the Russian Academy of Sciences developed a concept system that encompasses 1047 terms, each with a name, translation, and description, including references to other terms. This study aims to analyze the interconnections between the system's key network characteristics and validate the glossary's systematicity and principles of concept selection: hierarchy, balance, significance, and modularity. We confirmed the hierarchical organization of terms and identified clearly defined groups with established hierarchical structure of references. The research noted a reduction in the terms' structural significance and an increase in complexity when moving through the hierarchy from top to bottom, indicating modularity and balance. The analysis validated the terms' significance by their frequency of occurrence in control theory texts.
About the authors
Dmitry Aleksandrovich Novikov
V.A. Trapeznikov Institute of Control Sciences of RAS
Email: novikov@ipu.ru
Moscow
Dmitry Alekseevich Gubanov
V.A. Trapeznikov Institute of Control Sciences of RAS
Email: gubanov@ipu.ru
Moscow
References
- ГУБАНОВ Д.А., НОВИКОВ Д.А. Методы извлечения и анализа терминологических структур смежных пред-метных областей (на примере методологии) // Онтология проектирования. – 2018. – Т. 8, №3(29). – С. 347–365.
- ГУБАНОВ Д.А., НОВИКОВ Д.А., МАКАРЕНКО А.В. Методы анализа терминологической структуры пред-метной области // Управление большими системами. – 2013. – Вып. 43. – С. 5–33.
- Теория управления. Терминология. – Вып. 107. М.: Наука, 1988. – 56 с.
- Теория управления: словарь системы основных понятий. – Москва: УРСС, 2024. – 128 с.
- ASTRAKHANTSEV NA, FEDORENKO DG, TURDA-KOV D.YU. Methods for Automatic Term Recognition in Domain Specific Text Collections: A Survey // Programming and Computer Software. – 2015. – Vol. 41(6). – P. 336–349.
- BLOCH F., JACKSON M., TEBALDI P. Centrality Measures in Networks // Social Choice and Welfare. – 2023. – Vol. 61. – P. 413–453.
- CHEBOTAREV P.Yu., GUBANOV D.A. How to choose the most appropriate centrality measure? // arXiv: 2003.01052v1. – URL: https://arxiv.org/abs/2003.01052.
- Glossary of Control Engineering Terms. – URL: www.actc-control.com/glossary.
- KARBA R., KOCIJAN J., BAJD T. et al. Terminological Dictionary of Automatic Control, Systems and Robotics. – Heidelberg: Springer, 2024. – 249 p.
- MANNING C., SCHÜTZE H. Foundations of Statistical Natural Language Processing. – MIT press, 1999. – 620 p.
- WAN Z., MAHAJAN Y., KANG B. et al. A survey on Cen-trality Metrics and their Network Resilience Analysis // IEEE Access. – 2021. – Vol. 9. – P. 104 773–819.
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