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June 20, 2025Digital TransformationOpen Access

The Use of Large Language Models for the Analysis of Professional Competencies in the Regional Labor Market of the Republic of Belarus

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Authors

IKIryna Kalinouskaya

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Overview

Computational analysis demonstrates over 85% accuracy in extracting skill competencies from unstructured job postings, indicating language models can effectively map labor market demands.

Key Points

  • To develop an integrated framework that leverages large language models and big data analysis to extract, classify, and profile professional competencies from unstructured job advertisements.
  • Gathered job market vacancy descriptions using automated web scraping tools.
  • Processed raw data through a multi-level text cleaning and normalization pipeline.
  • Utilized large language models to identify competency clusters and generate structured skill profiles across professional groups.
  • Achieved accuracy and completeness rates exceeding 85% for extracting professional competency data from unstructured vacancy texts.
  • Successfully identified stable clusters of complementary skills and core competency combinations across diverse occupational sectors.

Cite This Study

Iryna Kalinouskaya (2025) studied this question.

synapsesocial.com/papers/6a186ea32a42b8bfbcc98e78https://doi.org/10.35596/1729-7648-2025-31-2-21-31
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