Main Article Content

Serhii Olizarenko
Vladimir Argunov


The possibilities of determining the semantic similarity of multilingual arbitrary-length text content have been investigated using their vector representations obtained within different multilingual models based on Transformer architecture. A comparative analysis of the Transformers has been performed to select the most advantageous model for this class of problems. Also, two new unique approaches to determining the semantic similarity of a multilingual text content have been developed to be used in the HIPSTO Open AI Information Discovery Platform, the challenge being to allow arbitrary text length. Experimental and research evidence is offered to support the new approaches as a solution to the semantic similarity problem.

Article Details

Information systems research
Author Biographies

Serhii Olizarenko, Kharkіv National University of Radio Electronics University, Kharkiv

Doctor of Technical Sciences, senior researcher, professor of the electronic computers department

Vladimir Argunov, HIPSTO, Kharkiv

Head of AI Research


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