Applied Sciences
OPEN ACCESS
Performance Optimization Of N-Gram Generation in Natural Language Processing Systems Through Parallel Computing
DOI
Crossref DOI
10.37547/tajas/Volume08Issue06-11
tajas
2026
VOL. 8
/ NO. 06
JUNE
RESEARCH OVERVIEW
Abstract
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.
RESEARCH TOPICS
Keywords
N-gram Generation
Natural Language Processing
Parallel Processing
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References
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