Building Data-Driven Occupation Taxonomies: A Bottom-Up Multi-Stage Approach via Semantic Clustering and Multi-Agent Collaboration (2025.emnlp-industry)
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| Challenge: | Existing methods for creating robust occupation taxonomies are slow and expensive . a robust taxonomy is critical for job recommendation and labor market intelligence applications . |
| Approach: | They propose a framework that automates creation of occupation taxonomies from job postings . they use global semantic clustering to distill core occupations, then a reflection-based multi-agent system to iteratively build a coherent hierarchy. |
| Outcome: | The proposed framework produces taxonomies that capture unique regional characteristics. |
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