A Characterization Methodology for Candidates and Recruiters Interaction in Online Recruitment Services

  • Alan Cardoso UFSJ
  • Fernando Mourão Seek AI Labs
  • Leonardo Rocha UFSJ


Online recruitment services have attracted an increasing number of candidates and recruiters who are looking for better job opportunities and the best professionals in their respective areas. These services, through search and recommendation systems, explore candidates and job profiles to identify the ideal candidates for each job vacancy. There are many challenges when we follow this scenario, such as reciprocal matches between vacancies and candidates, temporal dynamics (candidate/vacancy relationship varies over time) and imbalances between demand and supply between areas. Modeling the preferences and behavior of candidates and recruiters is an essential task for which improvements can be proposed by these services to mitigate their challenges. We present in this work a methodology that aims to help answer questions that may be asked about users preferences and behavior, extracting information that leads to improvements in existing functionality and the creation of new ones.We applied our methodology to actual data and questions, which were provided by Catho, the leading Latin American market company within this segment. In the analysis of results, we present opportunities for improvement in online recruitment services, such as the creation of a tool to help register job vacancies and resumes.
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CARDOSO, Alan; MOURÃO, Fernando; ROCHA, Leonardo. A Characterization Methodology for Candidates and Recruiters Interaction in Online Recruitment Services. In: ANAIS PRINCIPAIS DO SIMPÓSIO BRASILEIRO DE SISTEMAS MULTIMÍDIA E WEB (WEBMEDIA), 25. , 2019, Rio de Janeiro. Anais Principais do XXV Simpósio Brasileiro de Multimídia e Web. Porto Alegre: Sociedade Brasileira de Computação, oct. 2019 . p. 333-340.

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