Перегляд за автором "Shatalov, O."

Зараз показано 1 - 2 з 2
  • Зображення мініатюри
    Публікація
    Named Entity Recognition Problem for Long Entities in English Texts
    (2021) Shatalov, O.; Ryabova, N.
    This paper is related to the problem of natural language processing (NLP), namely the named entity recognition (NER). This paper reveals the features of named entities recognition in English texts using deep learning (DL). The peculiarity of the study was the rather long length of the presented named entities: many of them could include a rather large number of words. The main problem was the amount of text that had to be recognized as a single entity. The results of the research are described here show the effectiveness of using deep neural network architectures for the task of recognizing long named entities in texts in English.
  • Зображення мініатюри
    Публікація
    Towards Russian Text Generation Problem Using OpenAI’s GPT-2
    (CEUR Workshop Proceedings, 2021) Shatalov, O.; Ryabova, N. V.
    This work is devoted to Natural Language Generation (NLG) problem. The modern approaches in this area based on deep neural networks are considered. The most famous and promising deep neural network architectures that are related to this problem are considered, in particular, the most popular free software solutions for NLG based on Transformers architecture with pre-trained deep neural network models GPT-2 and BERT. The main problem is that the main part of already existing solutions is devoted to the English language. But there are few models that are able to generate text in Russian. Moreover, the text they generate often belongs to a general topic and not about a specific subject area. The object of the study is the generation of a contextually coherent narrow-profile text in Russian. Within the framework of the study, a model was trained for generating coherent articles of a given subject area in Russian, as well as a software application for interacting with it.