The Application of Artificial Intelligence Technologies as a Substitute for Reading and to Support and Enhance the Authoring of Scientific Review Articles

Abstract

To gain a comprehensive overview of new scientific findings with the enormous, ever-increasing amount of published information, we apply a new combinatorial approach that complements the process of reading scientific articles by supplementing artificial intelligence technologies. We present a combinatorial approach, which we illustrate in the form of a ''double funnel of artificial intelligence.'' Our approach suggests to largely increase the amount of data at the beginning of the data collection process and to subsequently clean and enrich the data set in order to gain much more knowledge at the end of the procedure compared to a ''classical'' literature review. We use natural language processing and text visualization techniques to uncover findings that are generally unbeknown to the human reader due to the inability to process very large amounts of text. By illustrating the individual steps using practical examples taken from use cases, we demonstrate the merits of our approach. With our methodology, we are able to reproduce findings from ''regular'' review papers; however, we discover additional and new findings in different fields, such as data science or medicine. We also point out the limitations of our approach. Finally, we make suggestions as to how the methodology could be further developed. INDEX TERMS Computational and artificial intelligence, document handling, fuzzy control, knowledge acquisition, pattern analysis, scientific publishing, text mining, text processing.

RegTech—the application of modern information technology in regulatory affairs: areas of interest in research and practice

“…The main focus areas currently seem to be the control of processes and the analysis and the alerting related to the content of the many guidelines that flood in on the enterprises and organizations. Here, researchers apply artificial intelligence technologies that are primarily related to natural language processing (Buchkremer et al, 2019). Since both topics (control and content alerts) are needed in other subject areas as well, we expect an extension of the terms RegTech to medicine and other industries in the future, both in practice and in the scientific literature.…”

“…Although the hits we reveal this way touch on the subject area, they do not influence the statements of our subsequent content analysis. Therefore, we refrain from an extensive literature research with methods of artificial intelligence or natural language processing (Buchkremer et al, 2019; Gampfer, et al, 2018). In combination with modern ITs, the application in regulatory affairs is currently almost exclusively depicted in the peer‐reviewed scientific literature related to the financial and banking sector.…”

“…The content of the articles is deliberately not part of the command search because it would have also included articles in which RegTech is only a marginal issue. Since title, abstract, and keywords contain a summary of the main content of an article, we ensure to find only articles in which RegTech is present as the main topic (based on Buchkremer et al, 2019). The literature research was carried out in December 2019.…”

Latent Dirichlet Allocation and t-Distributed Stochastic Neighbor Embedding Enhance Scientific Reading Comprehension of Articles Related to Enterprise Architecture

“…However, a solutionoriented approach can be found in the field of artificial intelligence. Modern methods, such as topic modeling, make it possible to carry out full-text analyses systematically [7]. Thus, a large number of publications in the field of EA can be investigated simultaneously.…”

“…Using topic modeling as an algorithm for the automatic evaluation of scientific publications is not new. Buchkremer et al [7] also used the methodology in their studies.…”