NLP-based intelligent text analysis system

Akbasheva Eugeniya Amirovna, Akbasheva Galina Amirovna, Tlupov Islam Zaurbekovich

The problem of representing the results of language models and evaluating their quality is understudied. This paper examines the application of language models and NLP techniques to develop an intelligent text analysis system. The idea is to use the capabilities of natural language processing algorithms to analyze semantics in order to demonstrate the possibilities of artificial intelligence for fast analysis of texts of any volume and subject matter. A graph representation of text is used to represent the results of the system.

Keywords:Natural language processing, language models, graph, machine learning, BERT model, SpaCy.