Using the bag of words algorithm in natural language processing

Abstract

A bag-of-words model is a digital representation of text to be
processed by machine learning algorithms. Using the Bag Of Words (BoW)
modeling algorithm, text can be converted and processed into digital
matrices. Bag of Words (BoW) is an algorithm that calculates the statistics
of a word in a document. The BoW algorithm is used in NLP applications
such as document comparison, information retrieval in search engines,
document classification, and thematic modeling. This article presents
the methods of converting Uzbek texts into digital form using the BoW
algorithm.