Kim et al., "Labor Space: A Unifying Representation of the Labor Market via Large Language Models" (2024)
2024-05-13 → 2026-08-14
Seongwoon Kim, Yong-Yeol Ahn, and Jaehyuk Park, Proceedings of the ACM on Web Conference 2024, 2441–2451 (2024)
Link | arXiv | PDF
@inproceedings{kim2024laborspace,
author = {Seongwoon Kim and Yong-Yeol Ahn and Jaehyuk Park},
title = {Labor Space: A Unifying Representation of the Labor Market via Large Language Models},
booktitle = {{Proceedings of the ACM on Web Conference 2024 (WWW)}},
pages = {2441--2451},
address = {Singapore, Singapore},
month = {5},
archivePrefix = {arXiv},
eprint = {2311.06310},
primaryClass = {physics.soc-ph},
doi = {10.1145/3589334.3645464},
year = {2024},
}
Uses large language models to embed occupations, industries, and skills in a common vector space, allowing relationships across labor-market taxonomies to be compared directly. It extends flow-based representations of the labor market toward a semantic representation based on textual descriptions.
Embedding, Occupation, Industry, Skill, Labor flow network