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Ontology engineering of automatic text processing methods

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 13 No. 6 (2023)

DOI
10.11591/ijece.v13i6.pp6620-6628
ISSN
2722-2578, 2088-8708
Published
2023-12-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Currently, ontologies are recognized as the most effective means of formalizing and systematizing knowledge and data in scientific subject area (SSA). Practice has shown that using ontology design patterns is effective in developing the ontology of scientific subject areas. This is due to the fact that scientific subject areas ontology, as a rule, contains a large number of typical fragments that are well described by patterns of ontology design. In the paper, we present an approach to ontology engineering of automatic text processing methods based on ontology design patterns. In order to get an ontology that would describe automatic text processing sufficiently fully, it is required to process a large number of scientific publications and information resources containing information from modeling area. It is possible to facilitate and speed up the process of updating ontology with information from such sources by using lexical and syntactic patterns of ontology design. Our ontology of automatic text processing will become the conceptual basis of an intelligent information resource on modern methods of automatic text processing, which will provide systematization of all information on these methods, its integration into a single information space, convenient navigation through it, as well as meaningful access to it.

Collaboration network of the authors

40 authors · 183 co-authorship links · 114 across different organisations · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • L. N. Gumilyov Eurasian National University
  • Dulaty University
  • Ministry of Education and Science of the Republic of Kazakhstan
  • Astana Medical University
  • Kazakh National Women's Teacher Training University
  • Kazakh Technology and Business University named after K.Kulazhanov
  • S.Seifullin Kazakh Agro Technical University
  • Other organisations
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Ainur AbduvalovaDulaty University4
Valentina E. MakhatovaKhalel Dosmukhamedov Atyrau University4
Nurbolat TasbolatulyAstana International University4
Sandugash SerikbayevaL. N. Gumilyov Eurasian National University4
Gulzira AbdikerimovaL. N. Gumilyov Eurasian National University3
Madina SambetbayevaMinistry of Education and Science of the Republic of Kazakhstan3
Sandugash SerikbayevaL. N. Gumilyov Eurasian National University3
Aigerim YerimbetovaMinistry of Education and Science of the Republic of Kazakhstan3
Ainur ShekerbekL. N. Gumilyov Eurasian National University2
Svetlana BeglerovaDulaty University2
Gulmira BekmagambetovaKazakh Technology and Business University named after K.Kulazhanov1
Makbal BaibulovaL. N. Gumilyov Eurasian National University1
Elena ZakharevichDulaty University1
Zhanat ManbetovaAffiliation unknown1
Moldir YessenovaL. N. Gumilyov Eurasian National University1
Gulden MurzabekovaS.Seifullin Kazakh Agro Technical University1
Nurbol KakabayevKokshetau State University1
Natalya GlazyrinaL. N. Gumilyov Eurasian National University1
Saltanat AdikanovaSarsen Amanzholov East Kazakhstan University1
Nurgul UzakkyzyL. N. Gumilyov Eurasian National University1
Rozamgul NiyazovaL. N. Gumilyov Eurasian National University1
B. SultanovaAffiliation unknown1
Elvira DzhaulybaevaAstana Medical University1
Kamshat ZhumakanovaKaraganda Medical University1
Bakhytgul RysbekkyzyAbylkas Saginov Karaganda Technical University1
Ainur OrazayevaL. N. Gumilyov Eurasian National University1
Gulmira ShangytbayevaAktobe Regional State University named after K.Zhubanov1
Assem GalymovaAffiliation unknown1
Ulzhalgas ZhunissovaAstana Medical University1
Aliya S. TergeussizovaAlmaty University of Power Engineering and Telecommunications1
Arailym TleubayevaAstana IT University1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Ontology engineering of automatic text processing methods</dc:title><dc:creator>Sadirmekova, Zhanna</dc:creator><dc:creator>Tussupov, Jamalbek</dc:creator><dc:creator>Murzakhmetov, Aslanbek</dc:creator><dc:creator>Zhidekulova, Gulkiz</dc:creator><dc:creator>Tungatarova, Aigul</dc:creator><dc:creator>Tulenbayev, Murat</dc:creator><dc:creator>Akhmetzhanova, Shynar</dc:creator><dc:creator>Altynbekova, Zhanar</dc:creator><dc:creator>Borankulova, Gauhar</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;span lang="EN-US"&amp;gt;Currently, ontologies are recognized as the most effective means of formalizing and systematizing knowledge and data in scientific subject area (SSA). Practice has shown that using ontology design patterns is effective in developing the ontology of scientific subject areas. This is due to the fact that scientific subject areas ontology, as a rule, contains a large number of typical fragments that are well described by patterns of ontology design. In the paper, we present an approach to ontology engineering of automatic text processing methods based on ontology design patterns. In order to get an ontology that would describe automatic text processing sufficiently fully, it is required to process a large number of scientific publications and information resources containing information from modeling area. It is possible to facilitate and speed up the process of updating ontology with information from such sources by using lexical and syntactic patterns of ontology design. Our ontology of automatic text processing will become the conceptual basis of an intelligent information resource on modern methods of automatic text processing, which will provide systematization of all information on these methods, its integration into a single information space, convenient navigation through it, as well as meaningful access to it.&amp;lt;/span&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2023-12-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v13i6.pp6620-6628</dc:identifier><dc:identifier>10.11591/ijece.v13i6.pp6620-6628</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 13 No 6 (2023); 6620</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>https://ijece.iaescore.com/index.php/IJECE/article/viewFile/32662/16986</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>