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A Data Driven bridge towards ESCO using AI algorithms (AI4ESCO)

Support the Member States, EURES members and partners to establish high-quality mapping-tables allowing for matching job vacancies and CVs in the European Job Mobility Portal. Main goals:

  1. derive a machine-readable structure of the lexicon used within the Italian National Occupation Taxonomy (CP2011);
  2. connect ESCO to Italian National Taxonomy by means of word-embedding similarities; this goal has been achieved in the rationale used by AI4ESCO, which employed state-of-the-art word-embedding algorithms to automatically suggest a match between CP-ESCO (and vice versa). Each match has been validated by a human-expert to confirm o refuse the matching;
  3. exploit on domain-experts to review and validate the results. This result has been achieved by employing labour market experts from ANPAL. The experts have been involved in many iterations of the mapping validation, resulting in a complete validation of both mappings (ESCO2CP and CP2ESCO).