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.
Giabelli, A., Malandri, L., Mercorio, F., Mezzanzanica, M., Seveso, A. (2021). NEO: A System for Identifying New Emerging Occupation from Job Ads. In 35th AAAI Conference on Artificial Intelligence, AAAI 2021 (pp.16035-16037). AAAI Press [10.1609/aaai.v35i18.18004].
NEO: A System for Identifying New Emerging Occupation from Job Ads
Giabelli, A;Malandri, L;Mercorio, F;Mezzanzanica, M;Seveso, A
2021
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.
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