Аннотация:
This paper focuses on the specifics of the an intelligent information system development for
supporting the processes of large volumes text data analysis and rephrasing based on deep
learning models. An overview of the key problems in the field of content analysis on the
Internet, in particular, text data, is carried out, ways of solving existing difficulties are
indicated, the artificial neural networks models using necessity to automate the process of
natural language processing is substantiated. Paper presents the results of LSTM and
Transformer models advantages analysis, software implementation within the framework of
an intelligent information system to support dialogue and text paraphrasing functions.
System’s design diagrams in UML are presented, its functionality is described and an
artificial neural network model’s effectiveness experimental study using the generated test
data sets is provided. As a result the paraphrases generation quality metrics were assessed
based on the use of the Loss and BLEU indicators. In the conclusion the authors describe
ways for the further system’s development and possible researches in related areas of natural
language processing based on deep learning.
