Design of Negative Sampling Strategies for Distantly Supervised Skill Extraction
Paper • 2209.05987 • Published
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This dataset contains an extension of the TECH subset form the SkillSpan dataset, in which spans of skill mentions in sentences have been labeled with corresponding ESCO skills (ESCO v1.1.0).
This dataset is part of a three-part evaluation dataset for skill extraction:
If you use this dataset, please include the following reference:
@inproceedings{decorte2022design,
articleno = {{4}},
author = {{Decorte, Jens-Joris and Van Hautte, Jeroen and Deleu, Johannes and Develder, Chris and Demeester, Thomas}},
booktitle = {{Proceedings of the 2nd Workshop on Recommender Systems for Human Resources (RecSys-in-HR 2022)}},
editor = {{Kaya, Mesut and Bogers, Toine and Graus, David and Mesbah, Sepideh and Johnson, Chris and Gutiérrez, Francisco}},
isbn = {{9781450398565}},
issn = {{1613-0073}},
language = {{eng}},
location = {{Seatle, USA}},
pages = {{7}},
publisher = {{CEUR}},
title = {{Design of negative sampling strategies for distantly supervised skill extraction}},
url = {{https://ceur-ws.org/Vol-3218/RecSysHR2022-paper_4.pdf}},
volume = {{3218}},
year = {{2022}},
}