MACHINE LEARNING ALGORITHMS IN TEXT CLASSIFICATION

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Authors: Nizamitdinov A.I, Inomov B.B.

Auhtors

Nizamitdinov A.I. – Doctor of Philosophy (PhD), Department of Programming and Information Technologies, Polytechnic Institute of Tajik Technical University, Khujand, Republic of Tajikistan, ahlidin@gmail.com.

Inomov B.B. – Phd student of specialty 6D070300- Information systems, Department of Programming and Information Technologies, Polytechnic Institute of Tajik Technical University, Khujand, Republic of Tajikistan behruzinomov@gmail.com.

Annotation

This article gives an overview of the available machine learning algorithms for classification problems, in particular in the problems of classifying texts of different language contexts. Text classification is one of the main tasks of computer linguistics. This direction has several main tasks, such as determining the thematic affiliation of texts, the author of the text, the emotional coloring of statements, etc. To ensure information and public safety in social networks, information sites, analysis of content containing illegal information is of great importance in telecommunication networks. The use of machine learning algorithms to solve text classification problems is a fairly common task today, since program complexes based on these algorithms have a rather high rating indicator in comparison with other classification approaches. The application and comparison of classification algorithms is a rather difficult task, since different input data can give different results. Therefore, software algorithms must be trained and tested on the same data sets.

Key words

algorithm, machine learning, text classification, data analysis

Language

English

Type of article

scientific

Year

2020

Page

34-46

References

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Publication date

05 Jun 2023