Дослідження методів автоматичного резюмування текстів новин

Abstract

The study delves into the challenge of summarization textual data in the Ukrainian language within the domain of computational linguistics, focusing on news summarization. Its primary objective is to assess and compare various approaches to language modeling tailored to the Ukrainian language in the context of news articles. The research entails the creation of a corpus of news articles, analysis of existing summarization methods, experimentation with different summarization techniques, and evaluation of the resulting models. Furthermore, the paper explores key linguistic areas such as phonology, morphology, syntax, semantics, and pragmatics, which serve as the theoretical foundation for effectively summarizing news articles computationally.