Computational linguistics and intelligent systems
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Item Unsupervised Open Relation Extraction(2021-05-04) Tarasenko, Yaroslav; Petrasova, Svitlana; National Technical University “Kharkiv Polytechnic Institute”The paper describes an approach to open relation extraction based on unsupervised machine learning. The state-of-the-art methods for extracting semantic relations are analyzed. The algorithm of automatic open relation extraction using statistical, syntactic and contextual information is proposed. The results of the study can be used in information retrieval, summarization, machine translation, question-answering systems, etc.Item An Approach to Extraction of Verb-Noun Patterns from News Data Stream(2021-05-04) Romanova, Uliana; Petrasova, Svitlana; National Technical University “Kharkiv Polytechnic Institute”The paper describes an approach to extraction of Verb-Noun patterns from news data stream. The linguistic tagging, namely algorithms for parsing, and methods for extracting collocations are analyzed. The algorithm for the automatic extraction of Verb collocations from the designed corpus of news texts is proposed. The Stanford Universal Dependencies parser is applied to identify Verb-Noun patterns. Then t-score is implemented for extracting collocations.Item Linguistic Features of Designing Open-Ended Test Systems(2021-05-04) Shapovalova, Anastasiia; Petrasova, Svitlana; National Technical University “Kharkiv Polytechnic Institute”The paper provides an algorithm of designing a test system for automated knowledge assessment through open-ended questions. The relevance of the use of open-ended tasks and problems of processing natural language answers are analyzed. The application of WordNet and regular expressions is proposed for designing samples of correct answers in the questionnaire.Item 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.Item Method for paraphrase extractionfrom the news text corpus(Lviv Politechnic Publishing House, 2019-04-18) Manuilov, Illia; Petrasova, Svitlana; National Technical University "Kharkiv Polytechnic Institute"The paper discusses the process of automatic extraction of paraphrases used in rewriting. The researchers propose the method for extracting paraphrases from English news text corpora. The method is based on both the developed syntactic rules to define phrases and synsets to identify synonymous words in the designed text corpus of BBC news. In order to implement the method, Natural Language Toolkit, Universal Dependencies parser and WordNet are used.Item Method for automatic collocation extraction from Ukrainian corpora(Lviv Polytechnic National University, 2018-06-25) Kuzmina, Maria; Petrasova, Svitlana; National Technical University "Kharkiv Polytechnic Institute"