An Overview of Existing Machine Learning Methods for Gender Classification of Names

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2021vVol_II___Proceedings_of_the_5th_International_conference_COLINS_2021_Workshop_Kharkiv_Ukraine_April_22-23_Shleiko_A-An_Overview_of_Existing_Machine_91-92.pdf (248.13 KB)
2021vVol_II___Proceedings_of_the_5th_International_conference_COLINS_2021_Workshop_Kharkiv_Ukraine_April_22-23_Shleiko_A-An_Overview_of_Existing_Machine_91-92__COVER.png (899.92 KB)

Date

2021-05-04

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Abstract

The paper presents an overview of the existing machine learning methods for solving the problem of gender classification of the authors of the written texts by names: substantiates the relevance of the research topic, analyzes the existing methods of solving the task and selects the direction of further research.

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Keywords

Gender classification, supervised machine learning, methods of classification

Citation

An Overview of Existing Machine Learning Methods for Gender Classification of Names / Anna Shleiko, Natalia Borysova, Zoia Kochuieva, Karina Melnyk // Computational linguistics and intelligent systems, 22-23 April 2021, Kharkiv. — Lviv ; Kharkiv, 2021. — Vol Vol. II : Proceedings of the 5th International conference, COLINS 2021, Workshop, Kharkiv, Ukraine, April 22-23. — P. 91–92.

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https://ena.lpnu.ua/handle/ntb/56805

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Computational linguistics and intelligent systems. – 2021 р.