NEO: A System for Identifying New Emerging Occupation from Job Ads

Authors

Anna Giabelli

Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy CRISP Research Centre, University of Milano-Bicocca, Milan, Italy

Lorenzo Malandri

Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy CRISP Research Centre, University of Milano-Bicocca, Milan, Italy

Fabio Mercorio

Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy CRISP Research Centre, University of Milano-Bicocca, Milan, Italy

Mario Mezzanzanica

Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy

Andrea Seveso

Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy CRISP Research Centre, University of Milano-Bicocca, Milan, Italy

Proceedings:

No. 18: AAAI-21 Student Papers and Demonstrations

Volume

Issue:

Proceedings of the AAAI Conference on Artificial Intelligence, 35

Track:

AAAI Demonstration Track

Downloads:

Download PDF

Abstract:

We demonstrate NEO, a tool for automatically enriching the European Occupation and Skill Taxonomy (ESCO) with terms that represents new occupations extracted from million Online Job Advertisements (OJAs). NEO proposes (i) a novel metric that allows one to measure the semantic similarity between words in a taxonomy, and (ii) a set of measures that estimate the adherence of new terms to the most suited taxonomic concept, enabling the user to evaluate the suggestions. To test its effectiveness, NEO has been evaluated over 2M+ 2018 UK job ads, along with a user-study to confirm the usefulness of NEO in the taxonomy enrichment task.

DOI:

10.1609/aaai.v35i18.18004

AAAI

Proceedings of the AAAI Conference on Artificial Intelligence, 35

Cookie	Duration	Description
cookielawinfo-checkbox-analytics	11 months	This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics".
cookielawinfo-checkbox-functional	11 months	The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional".
cookielawinfo-checkbox-necessary	11 months	This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary".
cookielawinfo-checkbox-others	11 months	This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other.
cookielawinfo-checkbox-performance	11 months	This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance".
viewed_cookie_policy	11 months	The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. It does not store any personal data.