Automatic Extraction of Scientific Information from Open Access Publications

Dmitry Aleksandrovich Akimov, Valery Evgenevich Sachkov, Ekaterina Olegovna Guryanova and Ilya Konstantinovich Shevtsov

The development of the intellectual assets of the state and regions depends on the proficiency level of researchers and the capabilities of the scientific infrastructure. It is important to understand which research areas constitute the current technological trends and solve pressing production problems. The current pace of know-how implementation has accelerated so much that resulted in a situation in which it became necessary to analyze and predict the development of specific scientific areas in order to maintain and develop the competitiveness of the industry in a given region. The present article deals with the model of automatic extraction of scientific information from the texts of open access publications based on the formalization of ontologies of the scientific topic areas at the targeted setting of the search engine. The model takes into account semantic features of the construction of scientific texts to extract scientific facts stated in the publication. The article presents the results of the search for scientific facts by means of the formation of associative spaces in the semantic vector field to identify markers of the scientific research development in the repository of scientific publications’ texts. It is proposed to create software for the intense semantic search of scientific facts and analysis of their development based on the mechanism of associations and ontological modeling of the activity level of scientific topics and analysis of the types of authors. The authors of the current work consider the results of the automatic search of scientific facts for further application in the analysis of the scientific community segments development in the regions and make the conclusion about the effectiveness of the involvement of the scientific community and specific authors of publications in the development of the regional potential in the R&D segment.

Volume 12 | 03-Special Issue

Pages: 383-391

DOI: 10.5373/JARDCS/V12SP3/20201273