Application of machine learning and natural language processing to develop a recommendation system for the selection of perfumery products

Abstract

Application of machine learning and natural language processing to develop a recommendation system for the selection of perfumery products

Smirnov V.K., Anikin A.V.,Litovkin D.V., Katyshev A.M.

Incoming article date: 19.01.2022

The paper discusses the use of machine learning in relation to natural language processing (sentiment analysis, semantic proximity analysis) to build a recommendation system for the choice of perfumery products. The topic of the work is relevant in view of the growth of the range of manufactured perfumery products and the complexity of its choice by consumers and promotion by manufacturers. The proposed approaches are relevant for solving this problem due to the accumulated textual reviews and reviews of perfumery products on various websites, including online stores.

Keywords: machine learning, natural language, sentiment analysis, distributive semantics, word2vec, recommender systems