LITERATURE STUDY OF GERMAN AND UZBEK LANGUAGES: A RANKING OF LINGUISTIC DISCOURSE MODELS
DOI:
https://doi.org/10.5281/zenodo.17417781Keywords:
Cross-linguistic Discourse Modeling, AHP-TF-IDF Framework, Computational Linguistics, Hierarchical Discourse Ranking, Syntactic Dependency Analysis, Network-Based Discourse Evaluation, Lexical Cohesion, Semantic Density.Abstract
This study aims to analyze linguistic discourse models in German and Uzbek using AHP, TF-IDF, syntactic
dependency, and network analysis. It also proposes a ranking-based evaluation method to identify discourse structures
and assess their hierarchical signifcance. By integrating computational linguistic techniques with a mixed-method
approach, the study develops a structured discourse ranking framework, classifying linguistic prominence into multiple
levels.
Key linguistic features including lexical cohesion, syntactic complexity, and semantic density are examined alongside
contextual relevance to sustain discourse patterns. The proposed framework enhances discourse modeling and facilitates
in-depth research using the AHP-TF-IDF methodology to explore, analyze, and summarize the linguistic structures shaped
by various contextual and syntactic factors.
This research contributes to resolving discourse-related challenges faced by Uzbek and German speakers in academic
and professional contexts by addressing computational limitations, linguistic typological differences, and structural
constraints. Additionally, it bridges the gap between applied discourse studies and broader linguistic research by
addressing cross-linguistic discourse variations.
By focusing on comparative linguistic analysis, this study establishes a stronger foundation for evaluating, comparing, and
overcoming the challenges of linguistic model adaptation. It offers insights benefcial to both researchers and language
practitioners across different linguistic backgrounds.
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