MATN AVTOMATIK ANNOTATSIYASI UCHUN NLP VA DEEP LEARNING’NI INTEGRATSIYALASHGAN PARALLEL MODELI

Authors

  • Mardiyev Muslimbek G‘ulom o‘g‘li Author

Keywords:

Kalit so‘zlar: matn annotatsiyasi, NLP, chuqur o‘rganish, transformer, BiLSTM, parallel model, semantik tahlil.

Abstract

Annotatsiya: Mazkur maqolada matnlarni avtomatik annotatsiyalash muammosi yechimiga qaratilgan integratsiyalashgan parallel model taklif etiladi. Model tabiiy tilni qayta ishlash (NLP) texnikalari va chuqur o‘rganish (Deep Learning) yondashuvlarini birlashtirib, matn mazmunidan kalit so‘zlar, mavzular va qisqacha izohlarni avtomatik aniqlaydi. Taklif etilgan yondashuvda BiLSTM va Transformer arxitekturasi asosida parallel ravishda o‘rganilgan xususiyatlar kontekstual chuqurlik va semantik aniqlikni oshirishda xizmat qiladi. SemEval va Reuters kabi standart korpuslar asosida o‘tkazilgan eksperimentlar modelning aniqlik (91.3%) va F1-ko‘rsatkichi (90.7%) bo‘yicha mavjud usullardan ustunligini ko‘rsatdi. Ushbu model katta hajmdagi matnlar bilan ishlovchi axborot tizimlarida samarali annotatsiya vositasi sifatida qo‘llanishi mumkin.

References

1. Qaiser, S., & Ali, R. (2018). Text mining: use of TF-IDF to examine the relevance of words to documents. International journal of computer applications, 181(1), 25-29.

2. Pay, T., Lucci, S., & Cox, J. L. (2019). An ensemble of automatic keyword extractors: TextRank, RAKE and TAKE. Computación y Sistemas, 23(3), 703-710.

3. Zhou, M., Duan, N., Liu, S., & Shum, H. Y. (2020). Progress in neural NLP: modeling, learning, and reasoning. Engineering, 6(3), 275-290.

4. Resnik, P., & Lin, J. (2010). Evaluation of NLP systems. The handbook of computational linguistics and natural language processing, 271-295.

5. Radim ˇRehurek, R. (2011). Scalability of semantic analysis in natural language processing (Doctoral dissertation, Masaryk University).

6. Agbemuko, D., Okokpujie, I., Salami, M., & Tartibu, L. K. (2024). Automated Data Extraction and Character Recognition for Handwritten Test Scripts Using Image Processing and Convolutional Neural Networks. Nigerian Journal of Technological Development, 21(4), 97-115.

7. Elova, D. (2022). Tabiiy tilni qayta ishlash tizimlari. Prospects of Uzbek applied philology, 1(1).

8. Memon, J., Sami, M., Khan, R. A., & Uddin, M. (2020). Handwritten optical character recognition (OCR): A comprehensive systematic literature review (SLR). IEEE access, 8, 142642-142668.

Published

2025-07-09

How to Cite

Mardiyev Muslimbek G‘ulom o‘g‘li. (2025). MATN AVTOMATIK ANNOTATSIYASI UCHUN NLP VA DEEP LEARNING’NI INTEGRATSIYALASHGAN PARALLEL MODELI. World Scientific Research Journal, 41(1), 79-86. https://scientific-jl.com/wsrj/article/view/24501