A Focused Analysis of the Intersection of Machine Learning and Intelligent Decision

Shuke Wang; Yan Xu

doi:10.54097/a7rmsf08

Authors

Shuke Wang
Yan Xu

DOI:

https://doi.org/10.54097/a7rmsf08

Keywords:

Machine Learning, Intelligent Decision, Bibliometric Analysis, Burst Detection Analysis, Evolutionary Analysis

Abstract

Machine learning and intelligent decision are important research topics, and the effective combination of the two is a current research hotspot. To further understand the outcomes of the collision of the two fields, this paper comprehensively analyzes the research dynamics of intelligent decision and machine learning from a scientometric perspective using two tools, VOS viewer and CiteSpace. This study provides a holistic insight that helps researchers to better understand the research field. The data analysis of the article is based on 2218 documents retrieved from the Web of Science database from 1990 to 2021. The paper investigates the collaborative network, bibliographic coupling of intelligent decision, and machine learning, revealing the distribution, and closeness of research in the field in terms of countries/regions, institutions, and authors. Further, the paper reveals the research hotspots and research frontiers of the topic through a series of visualization tools such as burst detection. On this basis, the article further discusses the current challenges and possible directions.

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