mlsanityData to 7 Oct 2026

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

arXiv 2402.05617 ↗First posted 8 Feb 2024cs.CLcited by 12

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 27 of its 61 references that are in the map. First posted on arXiv 8 Feb 2024.

Builds on

27 of 61 references.

References · 27

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  3. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,346
  4. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
  5. 2016Enriching Word Vectors with Subword Informationcited by 1,578
  6. 2020Don't Stop Pretraining: Adapt Language Models to Domains and Taskscited by 1,548
  7. 2022Text Embeddings by Weakly-Supervised Contrastive Pre-trainingcited by 1,216
  8. 2019SpanBERT: Improving Pre-training by Representing and Predicting Spanscited by 832
  9. 2020Language-agnostic BERT Sentence Embeddingcited by 621
  10. 2020Contrastive Learning with Hard Negative Samplescited by 619
  11. 2016Neural Architectures for Named Entity Recognitioncited by 548
  12. 2019CamemBERT: a Tasty French Language Modelcited by 368
15 more
  1. 2017Efficient Natural Language Response Suggestion for Smart Replycited by 228
  2. 2021TSDAE: Using Transformer-based Sequential Denoising Auto-Encoder for Unsupervised Sentence Embedding Learningcited by 116
  3. 2019Portuguese Named Entity Recognition using BERT-CRFcited by 73
  4. 2017Automated Phrase Mining from Massive Text Corporacited by 70
  5. 2022SkillSpan: Hard and Soft Skill Extraction from English Job Postingscited by 41
  6. 2018Learning Representations for Soft Skill Matchingcited by 19
  7. 2023Extreme Multi-Label Skill Extraction Training using Large Language Modelscited by 17
  8. 2022Design of Negative Sampling Strategies for Distantly Supervised Skill Extractioncited by 16
  9. 2023ESCOXLM-R: Multilingual Taxonomy-driven Pre-training for the Job Market Domaincited by 14
  10. 2023Large Language Models as Batteries-Included Zero-Shot ESCO Skills Matcherscited by 14
  11. 2021DataOps for Societal Intelligence: a Data Pipeline for Labor Market Skills Extraction and Matchingcited by 13
  12. 2022Skill Extraction from Job Postings using Weak Supervisioncited by 13
  13. 2020Deep Job Understanding at LinkedIncited by 12
  14. 2020Salience and Market-aware Skill Extraction for Job Targetingcited by 11
  15. 2022Is it Required? Ranking the Skills Required for a Job-Titlecited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 4; 2026: 7.

12 papers.

  1. 2024Natural Language Processing for Human Resources: A Surveycited by 9
  2. 2025Overview of the TalentCLEF 2025: Skill and Job Title Intelligence for Human Capital Managementcited by 3
  3. 2025Unified Work Embeddings: Contrastive Learning of a Bidirectional Multi-task Rankercited by 1
  4. 2025NLPnorth @ TalentCLEF 2025: Comparing Discriminative, Contrastive, and Prompt-Based Methods for Job Title and Skill Matchingcited by 0
  5. 2025Enhancing Job Matching: Occupation, Skill and Qualification Linking with the ESCO and EQF taxonomiescited by 0
  6. 2026Leveraging LLMs For Turkish Skill Extractioncited by 0
  7. 2026UniSkill: A Dataset for Matching University Curricula to Professional Competenciescited by 0
  8. 2026Job Skill Extraction via LLM-Centric Multi-Module Frameworkcited by 0
  9. 2026Chinese-SkillSpan: A Span-Level Dataset for ESCO-Aligned Competency Extraction from Chinese Job Adscited by 0
  10. 2026JobArabi: An Arabic Corpus and Analysis of Job Announcements from Social Mediacited by 0
  11. 2026Noise is Signal: Density-Based Outliers as Leading Indicators of Occupational Emergence in Labor Market Textcited by 0
  12. 2026TalentCLEF at CLEF2026: Skill and Job Title Intelligence for Human Capital Managementcited by 0