A predictive filtering approach for clarifying bibliometric datasets: an example on the research articles related to industry 4.0

ABSTRACT

This study proposes a filtering approach based on text classification and a fuzzy multi-criteria decision-making technique to select the relevant bibliometric data for further analyses in the scope of bibliometrics, scientometrics, and related methodologies. The proposed approach is illustrated on Industry 4.0 and internet of things which are the concepts that currently draw utmost attention with a growing number of research and applications. Accordingly, various findings are presented revealing the characteristics of the selected bibliometric data with the help of text and network analytics. The potential contribution of this study is two-fold such that the study not only suggests a novel approach for clarifying the retrieved bibliometric data but also emphasises the mainstream research areas and directions of Industry 4.0 along with the concept of the internet of things. Thus, an analysis framework with computing techniques has been used to reveal the characteristics of literature in a field of technology.