Computational linguistics and intelligent systems

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    Automated building and analysis of Ukrainian Twitter corpus for toxic text detection
    (Lviv Politechnic Publishing House, 2019-04-18) Bobrovnyk, Kateryna; Taras Shevchenko National University of Kyiv
    Toxic text detection is an emerging area of study in Inter-net linguistics and corpus linguistics. The relevance of the topic can be explained by the lack of Ukrainian social media text corpora that are publicly available. Research involves building of the Ukrainian Twitter corpus by means of scraping; collective annotation of 'toxic/non-toxic' texts; construction of the obscene words dictionary for future feature engineering; and models training for the task of text classi cation (com-paring Logistic Regression, Support Vector Machine, and Deep Neural Network).
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    Extraction of semantic relations from Wikipedia text corpus
    (Lviv Politechnic Publishing House, 2019-04-18) Shanidze, Olexandr; Petrasova, Svitlana; National Technical University "Kharkiv Polytechnic Institute"
    This paper proposes the algorithm for automatic extraction of semantic relations using the rule-based approach. The authors suggest identifying certain verbs (predicates) between a subject and an object of expressions to obtain a sequence of semantic relations in the designed text corpus of Wikipedia articles. The synsets from WordNet are applied to extract semantic relations between concepts and their synonyms from the text corpus.