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Документ Basic concepts of computer lexicography(Видавничий дім "Гельветика", 2023) Serdiukova, Olha; Lazareva, Olga; Cherniavska, InnaThe article is devoted to researching computer lexicography and aims at regarding basic concepts of the applied scientific discipline in linguistics. Such tasks of computer lexicography, as parsing, creating a lexical database, lexical analysis of electronic dictionaries, estimation of the number of multi-valued-single-valued words, automatic extraction of hyponym-hypernym relationships, displaying values when extracting from several dictionaries at once, defining a value within a single dictionary and extracting information using a set of monolingual and translation dictionaries are discussed. The major principles of a computer dictionary compiling and an example of a dictionary entry are provided. Such terms as lexeme, lemma and lemmatization are explained. Corpus lexicography as a relatively new branch of computer lexicography is overviewed. The authors also note that computational linguistics is closely related to the central problem of artificial intelligence. It is emphasized that although the aims of traditional and computer lexicography are mainly the same, their methods, tools and approaches differ significantly. It is shown that such features of electronic dictionaries as multifunctionality, the use of multimedia, possibility of updating, convenient search and many others provide considerable advantages over conventional paper dictionaries. Practical lexicography is defined as the process of compiling dictionaries of various types on the basis of theoretical developments. The process of creating electronic dictionaries is discussed. Depending on the purpose of the dictionary, its volume, the order of the words in it, the object of description and other criteria, dictionaries can be divided into various types. Such dictionary types as explanatory, translation, etymological, frequency etc. are described. It is concluded that for researchers working in the sphere of computer lexicography and other fields of applied linguistics, understanding of the basic principles, tasks and functionality of computer-based dictionaries is vital.Документ Применение масштабных лингвистических ресурсов для расширения онтологии предметной области (на примере области "Радиационная безопасность")(Технологический центр, 2014) Оробинская, Елена Александровна; Шаронова, Наталья Валерьевна; Дорошенко, Анастасия Юрьевна; Шоша, Жан-ЮгВ статье описан полуавтоматический метод расширения базовой онтологии для предметной области "радиационная безопасность", основанный на принципах NLP. Метод позволяет расширить онтологию новыми экземплярами и отношениями. Для решения проблемы неоднозначности слов был использован словарь синонимов. В работе представлены результаты эксперимента, выполненного для расширения онтологии новыми экземплярами, обнаруженными в специализированном текстовом корпусе.Документ Issues of Fact-based Information Analysis(2018) Sharonova, Natalia Valeriyevna; Doroshenko, Anastsiia; Cherednichenko, OlgaWith the recent growth of Internet, mobile and social networks the spread of fake news and click-baits increases drastically. Today, the fact retrieval system is one of the most effective tools for identifying the information for decision-making. We propose the approach based on factual information systematization. Different interpretations of the same phenomenon, as well as the inconsistency, inaccuracy or mismatch in information coming from different sources, lead to the task of factual information extraction. In this work, we explore how can natural language processing methods help to check contradictions and mismatches in facts automatically. The reference model of the factbased analytical system is proposed. It consists of such basic components as Document Search component, Fact retrieval component, Fact Analysis component, Visualization component, and Control component.Документ Similar Text Fragments Extraction for Identifying Common Wikipedia Communities(MDPI AG, Switzerland, 2018) Petrasova, S. V.; Khairova, N. F.; Lewoniewski, Włodzimierz; Mamyrbayev, Orken; Mukhsina, KuralaySimilar text fragments extraction from weakly formalized data is the task of natural language processing and intelligent data analysis and is used for solving the problem of automatic identification of connected knowledge fields. In order to search such common communities in Wikipedia, we propose to use as an additional stage a logical-algebraic model for similar collocations extraction. With Stanford Part-Of-Speech tagger and Stanford Universal Dependencies parser, we identify the grammatical characteristics of collocation words. WithWordNet synsets, we choose their synonyms. Our dataset includes Wikipedia articles from different portals and projects. The experimental results show the frequencies of synonymous text fragments inWikipedia articles that form common information spaces. The number of highly frequented synonymous collocations can obtain an indication of key common up-to-date Wikipedia communities.Документ Towards the ontology-based approach for factual information matching(Друкарня Мадрид, 2018) Sharonova, Natalia Valeriyevna; Doroshenko, Anastsiia; Cherednichenko, OlgaFactual information is information based on facts or relating to facts. The reliability of automatically extracted facts is the main problem of processing factual information. The fact retrieval system remains one of the most effective tools for identifying the information for decision-making. In this work, we explore how can natural language processing methods and problem domain ontology help to check contradictions and mismatches in facts automatically.Документ Ідентифікація смислових відношень у текстах вікіпедії для побудови семантичної мережі(Національний технічний університет "Харківський політехнічний інститут", 2019) Петрасова, Світлана Валентинівна; Шанідзе, Олександр Дмитрович; Швець, С. І.