Қазақ ұлттық қыздар педагогикалық университеті / Казахский национальный женский педагогический университет

Постоянный URI для этого сообществаhttps://cris.qyzpu.kz/handle/123456789/1

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2023 - 20243

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Тип доступа: НеизвестноАвтор: search.filters.author.Aslanbek Murzakhmetov

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    Тип записи:Публикация,
    Constructing the Terminological Core of NLP Ontology
    (2023-09-13)
    Zhanna B. Sadirmekova
    ;
    Madina Sambetbayeva
    ;
    Elmira Daiyrbayeva
    ;
    Aigerim Yerimbetova
    ;
    Zhanar Altynbekova
    The basis of any intellectual resource is a knowledge base, which, based on the basic terms of the field under consideration, builds relationships between them. Therefore, the first task to building multilingual information system using Natural language processing (NLP)in scientific and educational activities will be the development of a multilingual dictionary on modern NLP methods, including terms in Kazakh, English and Russian. For its construction, linguistic models for semantic dictionaries and thesauruses will be used, as well as methods of automatic extraction of terms from the corpus of texts of a given subject area. In this paper, a system of concepts of the NLP domain will be formalized, which will form the terminological core of the NLP ontology. To systematize information and provide support for multilingualism and accessibility, we plan to apply ontological engineering methods to systematize information and build the upper levels of the NLP ontology (its terminological core) using the dictionary of terms obtained at the previous stage. The ontology developed by us can later become the conceptual basis for a multilingual information system used in scientific and educational activities using NLP. This system will provide systematization of all information, convenient navigation on it, integration into a single information space, as well as access to it.
    Цитирования (OpenAlex) 3Цитирования (OpenCitations) 3
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    Тип записи:Публикация,
    Ontology engineering of automatic text processing methods
    (Institute of Advanced Engineering and Science (IAES), 2023-09-24)
    Zhanna B. Sadirmekova
    ;
    Jamalbek Tussupov
    ;
    Aslanbek Murzakhmetov
    ;
    Gulkiz Zhidekulova
    ;
    Aigul Turyszhanovna Tungatarova
    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.
    Цитирования (OpenAlex) 3Цитирования (OpenCitations) 4
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    Тип записи:Публикация,
    Approach to automating the construction and completion of ontologies in a scientific subject field
    (Institute of Advanced Engineering and Science (IAES), 2024-04-04)
    Zhanna B. Sadirmekova
    ;
    Aslanbek Murzakhmetov
    ;
    Ainur Abduvalova
    ;
    Zhanar Altynbekova
    ;
    Valentina E. Makhatova
    Domain ontologies facilitate the organization, sharing, and reuse of subject areas. Building a software ontology is labor-intensive and time-consuming. In the process of obtaining a software ontology, it is required to analyze a huge number of scientific publications relevant to the software being modeled. The process of ontology replenishing with information from a huge number of scientific publications can be facilitated and accelerated through the use of lexical-syntactic patterns of ontological design. In this paper, we consider the possibility of automated construction of scientific subject area ontologies based on a heterogeneous patterns system of ontological design. This system includes ontological design patterns and is intended for ontology developers. System also includes automatically built lexical and syntactic patterns, which help to automatic replenishment of the ontology with information extracted from natural language texts.
    Цитирования (OpenAlex) 3Цитирования (OpenCitations) 1