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

DOI:

https://doi.org/10.1609/aaai.v35i18.18004

Keywords:

Taxonomy Enrichment, Embedding Evaluation, Semantic Web

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.
AAAI-21 Proceedings Cover

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Published

2021-05-18

How to Cite

Giabelli, A., Malandri, L., Mercorio, F., Mezzanzanica, M., & Seveso, A. (2021). NEO: A System for Identifying New Emerging Occupation from Job Ads. Proceedings of the AAAI Conference on Artificial Intelligence, 35(18), 16035-16037. https://doi.org/10.1609/aaai.v35i18.18004

Issue

Vol. 35 No. 18: AAAI-21 Student Papers and Demonstrations

Section

AAAI Demonstration Track