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Large-Scale Linguistic Ontology as a Basis for Text Categorization of Legislative Documents., and . JURIX, volume 134 of Frontiers in Artificial Intelligence and Applications, page 109-110. IOS Press, (2005)Topic Models Can Improve Domain Term Extraction., , and . ECIR, volume 7814 of Lecture Notes in Computer Science, page 684-687. Springer, (2013)RUSSE'2020: Findings of the First Taxonomy Enrichment Task for the Russian language., , , and . CoRR, (2020)Taxonomy Enrichment with Text and Graph Vector Representations., , , , , and . CoRR, (2022)Multiple Evidence for Term Extraction in Broad Domains., and . RANLP, page 710-715. RANLP 2011 Organising Committee, (2011)Recognizing Names in Islam-Related Russian Twitter., and . DAMDID/RCDL, volume 2022 of CEUR Workshop Proceedings, page 246-251. CEUR-WS.org, (2017)Extracting Sentiment Attitudes from Analytical Texts via Piecewise Convolutional Neural Network., and . DAMDID/RCDL, volume 2277 of CEUR Workshop Proceedings, page 186-192. CEUR-WS.org, (2018)Итерационное извлечение шаблонов описания событий по новостным кластерам (Iterative Pattern Extraction Using News Clusters)., and . RCDL, volume 934 of CEUR Workshop Proceedings, page 292-298. CEUR-WS.org, (2012)Evaluating Sentiment Analysis Systems in Russian., and . BSNLP@ACL, page 12-17. Association for Computational Linguistics, (2013)Studying Taxonomy Enrichment on Diachronic WordNet Versions., , , and . COLING, page 3095-3106. International Committee on Computational Linguistics, (2020)