TY - GEN

T1 - A Computational Approach to Recognizing Poetry Genres in Uzbek Texts

AU - Mengliev, Davlatyor B.

AU - Barakhnin, Vladimir B.

AU - Saidov, Bobur R.

AU - Atakhanov, Mukhammadjon

AU - Eshkulov, Mukhriddin O.

AU - Ibragimov, Bahodir B.

PY - 2024/11/26

Y1 - 2024/11/26

N2 - In the research paper, the authors propose an algorithm for detecting poetic elements, words, and phrases in Uzbek texts. In addition, during analyzing the algorithm classifies poetic tokens in of the of 2 poetic genres (comedy, drama). In particular, the researchers trained a language model of artificial intelligence with an architectural combination of a convolutional neural network and long short-term memory. A custom language corpus was used as training data. This corpus was formed from more than 3,600 literary sentences, which in turn were selected from U zbek poetic works of the 20th century. Words and phrases in the corpus sentences were tagged according to the BIO-scheme, which the authors also talk about in the corresponding section of the article. Moreover, the authors also included information about the morphology of the U zbek language so that the context of this study was more understandable to all readers. In addition, the authors also conducted a comparative analysis of existing alternative works, where they provide the features of each similar work.

AB - In the research paper, the authors propose an algorithm for detecting poetic elements, words, and phrases in Uzbek texts. In addition, during analyzing the algorithm classifies poetic tokens in of the of 2 poetic genres (comedy, drama). In particular, the researchers trained a language model of artificial intelligence with an architectural combination of a convolutional neural network and long short-term memory. A custom language corpus was used as training data. This corpus was formed from more than 3,600 literary sentences, which in turn were selected from U zbek poetic works of the 20th century. Words and phrases in the corpus sentences were tagged according to the BIO-scheme, which the authors also talk about in the corresponding section of the article. Moreover, the authors also included information about the morphology of the U zbek language so that the context of this study was more understandable to all readers. In addition, the authors also conducted a comparative analysis of existing alternative works, where they provide the features of each similar work.

KW - Uzbek language

KW - Uzbek poetry

KW - algorithm development

KW - computational linguistics

KW - literary analysis

KW - machine learning

KW - natural language processing

KW - poetic evaluation

KW - poetry detection

KW - text analysis

UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85212080868&origin=inward&txGid=3fd2502aed1df5ed824b405c2fd28210

UR - https://www.mendeley.com/catalogue/1f9d0335-af8b-379a-8951-50547ba8020c/

U2 - 10.1109/SIBIRCON63777.2024.10758540

DO - 10.1109/SIBIRCON63777.2024.10758540

M3 - Conference contribution

SN - 9798331532024

T3 - 2024 IEEE International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2024

SP - 319

EP - 322

BT - 2024 IEEE International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2024

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2024 IEEE International Multi-Conference on Engineering, Computer and Information Sciences

Y2 - 30 September 2024 through 2 November 2024

ER -