Corpus Based Data Mining Applications in Computational Linguistics Authentic Compliant Letter Writing

The article considers the importance of corpus-based data mining in relation to the provision of compliant letter writing practices. The features of the linguistic patterns and application of natural language processing techniques in professional communication are formulated, an approach to creating an authentic complaint letter discourse model based on the linguistic nuances of a diverse organizational dataset is presented. The properties of the data-driven framework and the main requirements for ensuring compliance and accuracy are determined. The purpose of the study is to consider the applicability of computational linguistics in relation to compliance standards, to analyze its role and potential for improving the effectiveness and accessibility of professional correspondence. The experience of using corpus-based tools in linguistics and related areas, and the necessity of organizing a single compliance framework for cross-sectoral communication entities were analyzed. The properties of authenticity are also inherent in contextually compliant letters, with some of the latter's specific stylistic and structural traits. The basis of compliance-driven communication should be a standardized yet flexible framework with the following characteristics: support for context-sensitive phrasing, accuracy of content, adaptability, linguistic precision, semantic completeness of expressions, the ability to work on different contexts, and reliability of compliance outputs. The architecture of the framework should support multi-tiered functionality: the linguistic analysis level, the data modeling level, and the practical application level. The transition to data-driven linguistic modeling will create a new, compliance-oriented basis for providing authentic letter-writing tools and conducting scientific research. The transition to computationally enhanced linguistic models will lead to the fact that corpus-based insights can be applied to improve professional communication in the global workplace.

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Published
2024-12-11
DOI
https://doi.org/10.1145/3726122.3726167
Primary Topic
Natural Language Processing Techniques
Type
article
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article

Corpus Based Data Mining Applications in Computational Linguistics Authentic Compliant Letter Writing

Shirin Utkurovna Rakhimova, Nargiza Samandarova, Barno Shamsematova, Barchinoy Sultanova et al.
Natural Language Processing Techniques
article

Corpus Based Data Mining Applications in Computational Linguistics Authentic Compliant Letter Writing

Shirin Utkurovna Rakhimova, Nargiza Samandarova, Barno Shamsematova, Barchinoy Sultanova, Noila Mustafoyeva, Ikrom Merzaev
article en

Abstract

The article considers the importance of corpus-based data mining in relation to the provision of compliant letter writing practices. The features of the linguistic patterns and application of natural language processing techniques in professional communication are formulated, an approach to creating an authentic complaint letter discourse model based on the linguistic nuances of a diverse organizational dataset is presented. The properties of the data-driven framework and the main requirements for ensuring compliance and accuracy are determined. The purpose of the study is to consider the applicability of computational linguistics in relation to compliance standards, to analyze its role and potential for improving the effectiveness and accessibility of professional correspondence. The experience of using corpus-based tools in linguistics and related areas, and the necessity of organizing a single compliance framework for cross-sectoral communication entities were analyzed. The properties of authenticity are also inherent in contextually compliant letters, with some of the latter's specific stylistic and structural traits. The basis of compliance-driven communication should be a standardized yet flexible framework with the following characteristics: support for context-sensitive phrasing, accuracy of content, adaptability, linguistic precision, semantic completeness of expressions, the ability to work on different contexts, and reliability of compliance outputs. The architecture of the framework should support multi-tiered functionality: the linguistic analysis level, the data modeling level, and the practical application level. The transition to data-driven linguistic modeling will create a new, compliance-oriented basis for providing authentic letter-writing tools and conducting scientific research. The transition to computationally enhanced linguistic models will lead to the fact that corpus-based insights can be applied to improve professional communication in the global workplace.

Tashkent State Transport University (UZ), International Islamic Academy of Uzbekistan (UZ), Tashkent State University of Law (UZ), Tashkent State University of Economics (UZ)
Quality Education
Openalex Percentile: Top 72%
Natural Language Processing Techniques
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