Applied Sciences
| Open Access |
DOI: Performance Optimization Of N-Gram Generation in Natural Language Processing Systems Through Parallel Computing
Primova Mastura Hakim qizi , Senior Lecturer, Alisher Navoi Tashkent State University of Uzbek Language and Literature, Tashkent, UzbekistanAbstract
This study investigates optimization approaches for an N-gram generation module employed in natural language processing systems. The research focuses on enhancing the module's performance through the implementation of parallel processing techniques. Experimental evaluation demonstrated a substantial reduction in N-gram generation time, improved utilization of processor resources, and preservation of output accuracy. The findings indicate that the proposed optimization methods are effective for processing large-scale text corpora and can significantly improve the efficiency of N-gram-based language processing tasks.
Keywords
N-gram Generation, Natural Language Processing, Parallel Processing
References
https://groups.google.com/g/clojure/c/YtuQCrd8LZ8
Chew, Y. C., Mikami, Y., Marasinghe, C. A., & Nandasara, S. T. (2009). Optimizing n-gram order of an N-gram based language identification algorithm for 63 written languages. The International Journal on Advances in ICT for Emerging Regions, 2(2).
Elov B.B., Tojieva G.N., Tokhtaeva M. X., Jurayeva N.J., Primova M.H.: N-gram language model for Uzbek texts. International Conference on Trends in Sustainable Computing and Machine Intelligence (ICTSM 2025). – Bangkok, Thailand. – 19–20 September 2025. – P. 346-357. https://link.springer.com/chapter/10.1007/978-3-032-13177-5_27
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