Extracting key concepts and relationships between them from topical texts in Russian

Abstract

Extracting key concepts and relationships between them from topical texts in Russian

Denisov M.E., Katyshev A.M., Sychev O.A., Anikin A.V.

Incoming article date: 15.11.2022

The article discusses approaches to solving natural language processing problems such as extracting key concepts or terms, as well as semantic relationships between them to build data-driven IT solutions. The subject of the work is relevant due to the constant growth of volumes of low-structured and unstructured digital text. The extracted information can be used to improve numerous processes: automatic tagging, optimization of content search, construction of word clouds and navigation sections; furthermore, to create draft versions of dictionaries, thesauri, and even bases for expert systems.

Keywords: natural language processing, term, lemma, semantical relationship, statistical processing, machine learning, word2vec