Machine Learning and Natural Language Processing: Review of Models and Optimization Problems

Abstract

The purpose of this paper is to consider one of the most important modern technologies, namely: Natural Language Processing (NLP) and the machine learning algorithms related to it. The aim of the authors is to present the machine learning models in this interdisciplinary scientific field, which represents an intersection point of computer science, artificial intelligence, and linguistics. The machine learning techniques are classified and the corresponding models are briefly discussed. Different optimization approaches and problems for machine learning are considered. In this regard, some conclusions are drawn about the development trends in the area and the directions for future research.