人工智能研究趋势的定量估计:用Leimkuhler模型研究Bradford分布

Pub Date : 2023-08-06 DOI:10.5530/jscires.12.2.023

Solanki Gupta, Vivek Kumar Singh

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引用次数: 0

摘要

人工智能(AI)在人类生活各个领域的普遍应用导致了人工智能研究的惊人增长。人工智能的研究成果在过去十年中迅速增长。虽然一些科学计量学研究已经注意到出版物的增长，但实际上没有研究可以从开展和发表人工智能研究的领域和期刊的增长方面描述出版物的增长。本文试图利用Bradford生产率定律的Leimkuhler模型对人工智能研究发表进行定量估计，以填补这一研究空白。2011年至2020年期间在Web of Science索引的出版物用于分析。分析利用生产力分布及其特征解释了人工智能研究语料库的变化。定量研究结果支持了这样一种观点，即人工智能研究不仅在数量上有所增加，而且在更广泛的领域得到了应用。

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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Quantitative Estimation of Trends in Artificial Intelligence Research: A Study of Bradford Distributions using Leimkuhler Model

The ubiquitous applications of Artificial Intelligence (AI) in various domains of human life have resulted in a phenomenal increase in AI research. The research output in AI has grown rapidly during the last decade. While some scientometric studies have noted this growth in publications, there are virtually no studies that could characterize the growth in publications in terms of the increase in domains and journals in which AI research is being carried out and published. This article makes an attempt to fill this research gap by using the Leimkuhler model of Bradford’s law of productivity to produce quantitative estimates of AI research publishing. Publications indexed in Web of Science for the period 2011 to 2020 are used for analysis. The analysis explains the variation in the corpus of AI research using productivity distribution and its characteristics. The quantitative findings support the idea that AI research has not only increased in volume but also in terms of applications to a wider list of areas.

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