大文本数据在技术成熟度评估中的应用展望（出版物评论）

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2025-08-26 DOI:10.3103/S0005105525700505

I. V. Loginova, F. M. Grozovskiy, A. S. Piekalnits

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引用次数: 0

摘要

本文分析了传统技术成熟度评估方法的局限性，如s曲线、技术成熟度水平（TRL）、Gartner的炒作周期以及它们对专家意见的依赖。本文回顾了当前基于大文本数据分析和机器学习算法的方法，并展示了它们的优势。由于现有研究的系统化，揭示了使用机器学习方法向自动化技术成熟度评估过渡的前景。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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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 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.

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来源期刊

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS COMPUTER SCIENCE, INFORMATION SYSTEMS-

自引率

40.00%

发文量

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.