Prospects for Big Text Data Application in Technology Maturity Assessment (Publications Review)

The paper analyzes the limitations of conventional methods for assessing the maturity of technology, such as the S -curve, technology readiness level (TRL), Gartner’s hype cycle and their dependence on experts’ opinions. Current approaches to this task based on big text data analysis and machine lea...

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Bibliographic Details
Published inAutomatic documentation and mathematical linguistics Vol. 59; no. 3; pp. 145 - 153
Main Authors Loginova, I. V., Grozovskiy, F. M., Piekalnits, A. S.
Format Journal Article
LanguageEnglish
Published Moscow Pleiades Publishing 01.06.2025
Springer Nature B.V
Subjects
Computer Science
Data analysis
Information Processes
Information Storage and Retrieval
Machine learning
S curves
Technology assessment
technology readiness level (TRL)
machine learning
curve
big text data
Gartner Hype Cycle
technology maturity
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Summary:The paper analyzes the limitations of conventional methods for assessing the maturity of technology, such as the S -curve, technology readiness level (TRL), Gartner’s hype cycle and their dependence on experts’ opinions. Current approaches to this task based on big text data analysis and machine learning algorithms are reviewed, and their advantages are demonstrated. As a result of existing research systematization, the prospects of transition to automated technology maturity assessment using machine learning methods are revealed.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:0005-1055
1934-8371
DOI:10.3103/S0005105525700505