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Deep Learning-based Computational Job Market Analysis: A Survey on Skill Extraction and Classification from Job Postings

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Research
Peer-review

Open access

Abstract

Recent years have brought significant advances to Natural Language Processing (NLP), which enabled fast progress in the field of computational job market analysis. Core tasks in this application domain are skill extraction and classification from job postings. Because of its quick growth and its interdisciplinary nature, there is no exhaustive assessment of this field. This survey aims to fill this gap by providing a comprehensive overview of deep learning methodologies, datasets, and terminologies specific to NLP-driven skill extraction. Our comprehensive cataloging of publicly available datasets addresses the lack of consolidated information on dataset creation and characteristics. Finally, the focus on terminology addresses the current lack of consistent definitions for important concepts, such as hard and soft skills, and terms relating to skill extraction and classification.

Publication Information

Output type

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Research
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 1–15 (15 pages)

Publication milestones

  • Published - 03/2024

Publication status

Published - 03/2024

Publisher

Association for Computational Linguistics, United States

Host publication title

1st Workshop on Natural Language Processing for Human Resources

Related Event

Title

Natural Language Processing for Human Resources workshop

Event type

Workshop

Degree of recognition

International event

Date

22/03/2024 - 22/03/2024

Location

St. JuliansMalta