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April 25, 20260 citationsOpen Access

Identifying Smart Community Resilience Professional Roles Using Text Embeddings and Skill Similarity Analysis

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DZDanial ZareLSLuis Fernandez SanzMBMaría Teresa Villalba de Benito

Key Points

  • The aim is to identify and structure skills for emerging smart community professions using a data-driven approach.
  • Leveraged ESCO classification and MPNet-based text embeddings.
  • Performed cosine similarity analysis to group extracted skills into thematic categories.
  • Utilized transformer-based text generation models to create structured occupational descriptions.
  • Developed two new occupational profiles: Smart Community Resilience Engineer (SCRE) and Smart Community Resilient Solutions Procurer/Planner (SCRSP).
  • Grouped skills into competence domains for each role, supporting resilience in smart communities.

Abstract

This study proposes a data-driven approach to identifying and structuring the skills associated with emerging smart community professions by leveraging ESCO classification, MPNet-based text embeddings and cosine similarity analysis. The extracted skills were subsequently organised into thematic groups to provide a structured overview of the competence domains required for each role. In addition, several transformer-based text generation models were employed to generate structured occupational descriptions based on the identified skills and competence clusters. The results of this process led to the formalisation of two new occupational profiles designed to support resilience-oriented SCOs: the Smart Community Resilience Engineer (SCRE) and the Smart Community Resilient Solutions Procurer/Planner (SCRSP). These profiles aim to bridge existing gaps between technological innovation, governance processes, and resilience planning in smart community ecosystems. Keywords: Smart City, Smart Community, Resilience, Skill Framework, Text-embedding.

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Cite This Study

Zare et al. (2026) studied this question.

synapsesocial.com/papers/69ec5b0688ba6daa22dac919https://doi.org/10.5281/zenodo.19707439
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