NATURAL LANGUAGE PROCESSING METHODS FOR CONCEPT MAP MINING: THE CASE FOR ENGLISH, KAZAKH AND RUSSIAN TEXTS
Concept maps are used for knowledge visualization via representing an input text or domain at the conceptual level. Concept maps reflect the systemic relations between key concepts of a text/ domain and thereby contribute to a deeper understanding of text/domain ideas, save time spent on reading and...
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| Format: | Article |
| Language: | English |
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Al-Farabi Kazakh National University
2021-12-01
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| Series: | Вестник КазНУ. Серия математика, механика, информатика |
| Subjects: | |
| Online Access: | https://bm.kaznu.kz/index.php/kaznu/article/view/957/634 |
| _version_ | 1828051513699729408 |
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| author | A. B. Nugumanova Aizhan Soltangalienva Tlebaldinova Ye. M. Baiburin Ye. V. Ponkina |
| author_facet | A. B. Nugumanova Aizhan Soltangalienva Tlebaldinova Ye. M. Baiburin Ye. V. Ponkina |
| author_sort | A. B. Nugumanova |
| collection | DOAJ |
| description | Concept maps are used for knowledge visualization via representing an input text or domain at the conceptual level. Concept maps reflect the systemic relations between key concepts of a text/ domain and thereby contribute to a deeper understanding of text/domain ideas, save time spent on reading and analysis. However, the process of concept maps construction is laborious and time consuming. Currently, there is a lot of research on the idea of automatic generation concept map from natural language texts. The problem has a high practical value, but in theoretical terms, methods for its solution are mainly language-dependent. Such methods require high-quality annotated linguistic resources, which is a serious problem for low-resource languages like Kazakh. In this work, we analyze the issues related to language-dependent approaches and present our experimental work on automatic generating concept maps from English, Kazakh and Russian texts. We use a well-known language-dependent method called ReVerb which was originally developed for English, and on the example of this method we explore the issues that we have encountered in the case of Kazakh and Russian languages. |
| first_indexed | 2024-04-10T19:40:01Z |
| format | Article |
| id | doaj.art-93b494ca01e94dfb980a767e80d253d9 |
| institution | Directory Open Access Journal |
| issn | 1563-0277 2617-4871 |
| language | English |
| last_indexed | 2024-04-10T19:40:01Z |
| publishDate | 2021-12-01 |
| publisher | Al-Farabi Kazakh National University |
| record_format | Article |
| series | Вестник КазНУ. Серия математика, механика, информатика |
| spelling | doaj.art-93b494ca01e94dfb980a767e80d253d92023-01-29T12:24:00ZengAl-Farabi Kazakh National UniversityВестник КазНУ. Серия математика, механика, информатика1563-02772617-48712021-12-01112493108https://doi.org/10.26577/JMMCS.2021.v112.i4.08NATURAL LANGUAGE PROCESSING METHODS FOR CONCEPT MAP MINING: THE CASE FOR ENGLISH, KAZAKH AND RUSSIAN TEXTSA. B. NugumanovaAizhan Soltangalienva Tlebaldinova0Ye. M. BaiburinYe. V. PonkinaВосточно-Казахстанский университет имени С.АманжоловаConcept maps are used for knowledge visualization via representing an input text or domain at the conceptual level. Concept maps reflect the systemic relations between key concepts of a text/ domain and thereby contribute to a deeper understanding of text/domain ideas, save time spent on reading and analysis. However, the process of concept maps construction is laborious and time consuming. Currently, there is a lot of research on the idea of automatic generation concept map from natural language texts. The problem has a high practical value, but in theoretical terms, methods for its solution are mainly language-dependent. Such methods require high-quality annotated linguistic resources, which is a serious problem for low-resource languages like Kazakh. In this work, we analyze the issues related to language-dependent approaches and present our experimental work on automatic generating concept maps from English, Kazakh and Russian texts. We use a well-known language-dependent method called ReVerb which was originally developed for English, and on the example of this method we explore the issues that we have encountered in the case of Kazakh and Russian languages.https://bm.kaznu.kz/index.php/kaznu/article/view/957/634concept mapsconcept map miningnatural language processinglow-resource languagesr language |
| spellingShingle | A. B. Nugumanova Aizhan Soltangalienva Tlebaldinova Ye. M. Baiburin Ye. V. Ponkina NATURAL LANGUAGE PROCESSING METHODS FOR CONCEPT MAP MINING: THE CASE FOR ENGLISH, KAZAKH AND RUSSIAN TEXTS Вестник КазНУ. Серия математика, механика, информатика concept maps concept map mining natural language processing low-resource languages r language |
| title | NATURAL LANGUAGE PROCESSING METHODS FOR CONCEPT MAP MINING: THE CASE FOR ENGLISH, KAZAKH AND RUSSIAN TEXTS |
| title_full | NATURAL LANGUAGE PROCESSING METHODS FOR CONCEPT MAP MINING: THE CASE FOR ENGLISH, KAZAKH AND RUSSIAN TEXTS |
| title_fullStr | NATURAL LANGUAGE PROCESSING METHODS FOR CONCEPT MAP MINING: THE CASE FOR ENGLISH, KAZAKH AND RUSSIAN TEXTS |
| title_full_unstemmed | NATURAL LANGUAGE PROCESSING METHODS FOR CONCEPT MAP MINING: THE CASE FOR ENGLISH, KAZAKH AND RUSSIAN TEXTS |
| title_short | NATURAL LANGUAGE PROCESSING METHODS FOR CONCEPT MAP MINING: THE CASE FOR ENGLISH, KAZAKH AND RUSSIAN TEXTS |
| title_sort | natural language processing methods for concept map mining the case for english kazakh and russian texts |
| topic | concept maps concept map mining natural language processing low-resource languages r language |
| url | https://bm.kaznu.kz/index.php/kaznu/article/view/957/634 |
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