Abstract
With the rapid and continuous advancements in technology, as well as the constantly evolving competences required in the field of engineering, there is a critical need for the harmonization and unification of engineering professional figures or archetypes. The current limitations in tymely defining and updating engineers' archetypes are attributed to the absence of a structured and automated approach for processing educational and occupational data sources that evolve over time. This study aims to enhance the definition of professional figures in engineering by automating archetype definitions through text mining and adopting a more objective and structured methodology based on topic modeling. This will expand the use of archetypes as a common language, bridging the gap between educational and occupational frameworks by providing a unified and up-to-date engineering professional figure tailored to a specific period, specialization type, and level. We validate the automatically defined industrial engineer archetype against our previously manually defined profile.
| Original language | English |
|---|---|
| Article number | 103996 |
| Number of pages | 17 |
| Journal | Computers in Industry |
| Volume | 152 |
| Early online date | 8 Aug 2023 |
| DOIs | |
| Publication status | Published - Nov 2023 |
Bibliographical note
Publisher Copyright:© 2023 The Authors
Keywords
- Archetype
- Engineering
- Industry 4.0
- Latent dirichlet allocation
- Professional profile
- Text mining
ASJC Scopus subject areas
- General Computer Science
- General Engineering