TY - GEN

T1 - Development of a Legal Document Recognition Algorithm for the Karakalpak Language

AU - Mengliev, Davlatyor B.

AU - Barakhnin, Vladimir B.

AU - Eshkulov, Mukhriddin O.

AU - Allamov, Oybek T.

AU - Ibragimov, Bahodir B.

AU - Khudaybergenov, Timur A.

PY - 2024/11/26

Y1 - 2024/11/26

N2 - In this study, the authors propose an algorithm for recognizing legal documents in Karakalpak texts. To develop such an algorithm, similar scientific works were studied, the relevance of the current work and the problems that need to be solved were identified. The proposed algorithm is developed based on traditional rules, which include the rules of morphology of the Karakalpak language, as well as a dictionary of tagged words used to identify legal words and phrases from texts. The dictionary used contains more than 12,000 tagged words, which include both word roots and other forms concatenated to grammatical affixes. The authors also tested the algorithm, where high accuracy in identifying the necessary words was achieved. In particular, three samples were formed, each of which contained words and phrases of legal terminology in a certain amount. In conclusion, the authors added information regarding the proposed improvements and further prospects for the development of the algorithm.

AB - In this study, the authors propose an algorithm for recognizing legal documents in Karakalpak texts. To develop such an algorithm, similar scientific works were studied, the relevance of the current work and the problems that need to be solved were identified. The proposed algorithm is developed based on traditional rules, which include the rules of morphology of the Karakalpak language, as well as a dictionary of tagged words used to identify legal words and phrases from texts. The dictionary used contains more than 12,000 tagged words, which include both word roots and other forms concatenated to grammatical affixes. The authors also tested the algorithm, where high accuracy in identifying the necessary words was achieved. In particular, three samples were formed, each of which contained words and phrases of legal terminology in a certain amount. In conclusion, the authors added information regarding the proposed improvements and further prospects for the development of the algorithm.

KW - Karakalpak language

KW - NLP

KW - algorithm testing

KW - annotated dictionary

KW - legal document recognition

KW - linguistic resources

KW - low-resource language

KW - morphological analysis

KW - rule-based algorithm

KW - text tokenization

UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85212092216&origin=inward&txGid=50a189d008719dc9c313fbd29622cce3

UR - https://www.mendeley.com/catalogue/015c4969-ba88-3319-b8e6-8093da50dff8/

U2 - 10.1109/SIBIRCON63777.2024.10758548

DO - 10.1109/SIBIRCON63777.2024.10758548

M3 - Conference contribution

SN - 9798331532024

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

SP - 323

EP - 326

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 -