Neurocomputer System of Semantic Analysis of the Text in the Kazakh Language
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AHAQP4YKF" target="_blank" >RIV/00216208:11320/25:HAQP4YKF - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85191592513&doi=10.1145%2f3652159&partnerID=40&md5=d1cc060a0619c0201dc0b3d6cf933c26" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85191592513&doi=10.1145%2f3652159&partnerID=40&md5=d1cc060a0619c0201dc0b3d6cf933c26</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3652159" target="_blank" >10.1145/3652159</a>
Alternative languages
Result language
angličtina
Original language name
Neurocomputer System of Semantic Analysis of the Text in the Kazakh Language
Original language description
The purpose of the study is to solve an extreme mathematical problem-semantic analysis of natural language, which can be used in various fields, including marketing research, online translators, and search engines. When training the neural network, data training methods based on the latent Dirichlet allocation model and vector representation of words were used. This study presents the development of a neurocomputer system used for the purpose of semantic analysis of the text in the Kazakh language, based on machine learning and the use of the latent Dirichlet allocation model. In the course of the study, the stages of system development were considered, regarding the text recognition algorithm. The Python programming language was used as a tool using libraries that greatly simplify the process of creating neural networks, including the Keras library. An experiment was conducted with the involvement of experts to test the effectiveness of the system, the results of which confirmed the reliability of the data provided by the system. The papers of modern computer linguists dealing with the problems of natural language processing using various technologies and methods are considered. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
ACM Transactions on Asian and Low-Resource Language Information Processing
ISSN
2375-4699
e-ISSN
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Volume of the periodical
23
Issue of the periodical within the volume
4
Country of publishing house
US - UNITED STATES
Number of pages
15
Pages from-to
1-15
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85191592513