LITERATURE STUDY OF GERMAN AND UZBEK LANGUAGES: A RANKING OF LINGUISTIC DISCOURSE MODELS

Rakhmonov Abdulaziz Batir ugli

Innovation science and technologiy · 2025-yil

Annotatsiya

This study aims to analyze linguistic discourse models in German and Uzbek using AHP, TF-IDF, syntacticdependency, and network analysis. It also proposes a ranking-based evaluation method to identify discourse structuresand assess their hierarchical signifcance. By integrating computational linguistic techniques with a mixed-methodapproach, the study develops a structured discourse ranking framework, classifying linguistic prominence into multiplelevels.Key linguistic features including lexical cohesion, syntactic complexity, and semantic density are examined alongsidecontextual relevance to sustain discourse patterns. The proposed framework enhances discourse modeling and facilitatesin-depth research using the AHP-TF-IDF methodology to explore, analyze, and summarize the linguistic structures shapedby various contextual and syntactic factors.This research contributes to resolving discourse-related challenges faced by Uzbek and German speakers in academicand professional contexts by addressing computational limitations, linguistic typological differences, and structuralconstraints. Additionally, it bridges the gap between applied discourse studies and broader linguistic research byaddressing cross-linguistic discourse variations.By focusing on comparative linguistic analysis, this study establishes a stronger foundation for evaluating, comparing, andovercoming the challenges of linguistic model adaptation. It offers insights benefcial to both researchers and languagepractitioners across different linguistic backgrounds.

Maqola ma’lumotlari
MualliflarRakhmonov Abdulaziz Batir ugli
JurnalInnovation science and technologiy
Nashr sanasi2025-03-01
Jild1
Son2
Betlar36-42
TilIngliz
DOI10.5281/zenodo.17417781

Kalit so‘zlar

Cross-linguistic Discourse Modeling, AHP-TF-IDF Framework, Computational Linguistics, Hierarchical Discourse Ranking, Syntactic Dependency Analysis, Network-Based Discourse Evaluation, Lexical Cohesion, Semantic Density.

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