mlsanityData to 7 Oct 2026

DataOps for Societal Intelligence: a Data Pipeline for Labor Market Skills Extraction and Matching

arXiv 2104.01966 ↗First posted 5 Apr 2021cs.AIcited by 13

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Abstract (arXiv)

Big Data analytics supported by AI algorithms can support skills localization and retrieval in the context of a labor market intelligence problem. We formulate and solve this problem through specific DataOps models, blending data sources from administrative and technical partners in several countries into cooperation, creating shared knowledge to support policy and decision-making. We then focus on the critical task of skills extraction from resumes and vacancies featuring state-of-the-art machine learning models. We showcase preliminary results with applied machine learning on real data from the employment agencies of the Netherlands and the Flemish region in Belgium. The final goal is to match these skills to standard ontologies of skills, jobs and occupations.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Builds on 2 of its 16 references that are in the map. First posted on arXiv 5 Apr 2021.

Builds on

2 of 16 references.

References · 2

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019How multilingual is Multilingual BERT?cited by 642

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Citing papers per year: 2022: 6; 2023: 2; 2024: 5.

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