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

Elena Senger, Mike Zhang, Rob van der Goot, Barbara Plank

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

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 emerging 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 and classification. 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.

OriginalsprogEngelsk
TitelNLP4HR 2024 - 1st Workshop on Natural Language Processing for Human Resources, Proceedings of the Workshop
RedaktørerEstevam Hruschka, Thom Lake, Naoki Otani, Tom Mitchell
Antal sider15
ForlagAssociation for Computational Linguistics, ACL Anthology
Publikationsdato2024
Sider1-15
ISBN (Elektronisk)9798891760769
StatusUdgivet - 2024
Begivenhed1st Workshop on Natural Language Processing for Human Resources, NLP4HR 2024 - St. Julian's, Malta
Varighed: 22 mar. 2024 → …

Konference

Konference1st Workshop on Natural Language Processing for Human Resources, NLP4HR 2024
Land/OmrådeMalta
BySt. Julian's
Periode22/03/2024 → …
SponsorMegagon Labs
NavnNLP4HR 2024 - 1st Workshop on Natural Language Processing for Human Resources, Proceedings of the Workshop

Bibliografisk note

Publisher Copyright:
© 2024 Association for Computational Linguistics.

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