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Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
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A Bibliometric Perspective on AI Research for Job-Résumé Matching.

Sergio Rojas-Galeano1, Jorge Posada2, Esteban Ordoñez2

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Summary
This summary is machine-generated.

This study used bibliometrics to map the evolution of AI in recruitment. It reveals research trends and paradigm shifts in using artificial intelligence for automated resume screening and candidate selection.

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Area of Science:

  • Information Science
  • Computer Science
  • Human Resources Management

Background:

  • Traditional recruitment relies on human experts to screen résumés and match candidate skills to job requirements.
  • Advances in Artificial Intelligence (AI), particularly in text analytics and Natural Language Processing (NLP), offer potential for automating parts of the recruitment process.
  • The application of AI algorithms for information extraction, parsing, representation, and matching of résumés and job descriptions is an emerging research area.

Purpose of the Study:

  • To comprehensively understand the evolution of research in applying AI to personnel selection.
  • To identify key trends, dynamics, structures, and influential elements within this research field.
  • To map the research landscape using a multifaceted bibliometric approach.

Main Methods:

  • A bibliometric analysis was conducted on a publication record.
  • Data sources included Scopus and Google Scholar bibliographic databases.
  • The approach involved identifying trends, dynamics, structures, and visual mapping of topics, papers, authors, and institutions.

Main Results:

  • The bibliometric approach provided a more comprehensive overview of research evolution compared to traditional literature reviews.
  • Key research trends, influential publications, prominent authors, and leading universities in AI-driven recruitment were identified.
  • Significant paradigm shifts in the research field, from early stages to recent developments, were clearly delineated.

Conclusions:

  • Bibliometrics is an effective method for analyzing the evolution of scientific fields like AI in recruitment.
  • The study successfully mapped the research landscape, highlighting its development and key contributors.
  • This approach offers valuable insights for future research directions and understanding the impact of AI on personnel selection.