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NTIS 바로가기Procedia computer science, v.123, 2018년, pp.424 - 431
Sboev, Alexander (National Research Centre ‘Kurchatov Institute’, Moscow, Russian Federation) , Moloshnikov, Ivan (National Research Centre ‘Kurchatov Institute’, Moscow, Russian Federation) , Gudovskikh, Dmitry (National Research Centre ‘Kurchatov Institute’, Moscow, Russian Federation) , Selivanov, Anton (National Research Centre ‘Kurchatov Institute’, Moscow, Russian Federation) , Rybka, Roman (National Research Centre ‘Kurchatov Institute’, Moscow, Russian Federation) , Litvinova, Tatiana (National Research Centre ‘Kurchatov Institute’, Moscow, Russian Federation)
Abstract In this paper we compare accuracies of solving the task of gender identification of RusPro-filing texts without gender deception on base of two types of data-driven modeling approaches: on the one hand, well-known conventional machine learning algorithms, such as Support Vector machine, Gr...
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EACL Kutuzov 2017 99 2017 Building web-interfaces for vector semantic models with the webvectors toolkit
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10.1109/CSCI.2016.0210 Aleksandr Sboev, Tatiana Litvinova, Irina Voronina, Dmitry Gudovskikh, and Roman Rybka. Deep learning network models to categorize texts according to author’s gender and to identify text sentiment. In Computational Science and Computational Intelligence (CSCI), 2016 International Conference on, pages 1101-1106. IEEE, 2016.
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