Sentiment Classification of Russian Texts Using Automatically Generated Thesaurus

Keywords

Thesaurus, Computer science, Classifier (UML), Natural language processing, Artificial intelligence

References

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• A Review of Sentiment Analysis Research in Chinese LanguageHaiyun Peng, Erik Cambria, Amir Hussain — 2017
• Analysis of Influence of Different Relations Types on the Quality of Thesaurus Application to Text Classification ProblemsNadezhda Lagutina, Ksenia Lagutina, Ivan Shchitov — 2019
• Sentiment classification of long newspaper articles based on automatically generated thesaurus with various semantic relationshipsIvan Shchitov, Ksenia Lagutina, Nadezhda Lagutina — 2017
• Semantic-Syntactic Analysis for Question Answering and Definition ExtractionArtem Shelmanov, M. A. Kamenskaya, M. I. Ananyeva — 2017
• Analysis of Influence of Different Relations Types on the Quality of Thesaurus Application to Text Classification ProblemsNadezhda Lagutina, Ksenia Lagutina, Ivan Shchitov — 2017

Cited by

• Sentiment Classification into Three Classes Applying Multinomial Bayes Algorithm, N-Grams, and ThesaurusKsenia Lagutina, Vladislav Larionov, Vladislav Petryakov — 2019
• The Applications of Sentiment Analysis for Russian Language Texts: Current Challenges and Future PerspectivesSergey Smetanin — 2020
• Empirical Comparison of Word Similarity Measures Based on Co-Occurrence, Context, and a Vector Space ModelNatsuki Kadowaki, Kazuaki Kishida — 2020
• Deep transfer learning baselines for sentiment analysis in RussianSergey Smetanin, Mikhail Komarov — 2021
• Multi-label Classification Based on Domain Analysis in Fixed Point MethodAnna Berger, С. А. Гуда — 2021

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