Abstract
Reviewing the literature is one of the key elements of scientific research that allows you to identify existing solutions and research niches. However, it can be difficult for researchers to find relevant scientific articles related to the research topic. A limited number of available sources of information, diverse ways of describing them, and a multitude of scientific publications mean that scientists often have to spend a lot of time and effort to find the information they need. For this reason, we propose a solution for text analysis and its presentation in the form of a graph visualization. In our research, we used Natural Language Processing (NLP) methods and word weighting measures such as TF and TF-IDF. In addition, knowledge graphs were used to present the results visually. The conducted research was based on the analysis of the content of scientific articles, which allowed to draw important conclusions related to the presentation of texts in graphic form. Experimental results also identified potential methods and suggestions for literature reviews in specific fields of science. The analysis of the methods used and the results obtained allowed for a better understanding of the potential of natural language processing and graph text representation in the analysis of scientific articles.
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