A changing job market, influenced by different factors such as globalization and
demographic growth, urges close monitoring. The digitization of the job market has given the …

Skill Extraction (SE) is an important and widely-studied task useful to gain insights into labor
market dynamics. However, there is a lacuna of datasets and annotation guidelines; …

In this paper, we compare different methods to extract skill demand from the text of job
descriptions. We propose the fraction of wage variation explained by the extracted skills as a …

The rapidly evolving field of Data Operations (DataOps) is essential for enhancing data
management within large-scale enterprises. However, persistent challenges, such as …

The job market is evolving continuously due to changes in economic landscapes,
technological improvements, and skill requirements. In the era of digitalization, a wealth of …

Skill Classification (SC) is the task of classifying job competences from job postings. This
work is the first in SC applied to Danish job vacancy data. We release the first Danish job …

We present SkillGPT, a tool for skill extraction and standardization (SES) from free-style job
descriptions and user profiles with an open-source Large Language Model (LLM) as …

The goal of Digital Transformation of the Public Sector is the achievement of a better quality
of life for citizens, via a more responsive and transparent administration and governance. By …

The increasing number of benchmarks for Natural Language Processing (NLP) tasks in the
computational job market domain highlights the demand for methods that can handle job …

Aggregated data obtained from job postings provide powerful insights into labor market
demands, and emerging skills, and aid job matching. However, most extraction approaches …