Labour Market Intelligence for Supporting Decision Making

نویسندگان

  • Roberto Boselli
  • Mirko Cesarini
  • Fabio Mercorio
  • Mario Mezzanzanica
چکیده

Over the past decade, a growing number of employers has been using the Web for advertising job opportunities through Web job vacancies, that usually specify a job position, along with a set of skills a candidate should possess. Reasoning with these Web job advertisements can effectively support the decision marking processes of several labour market stakeholders, including public organisations, educational and employment agencies, and analysts as well. Here, Labour Market Intelligence refers to the design and definition of automated methodologies and tools for supporting real-time labour market monitoring at a very fine-grained level. This, in turn, represents a competitive advantage to labour market stakeholders with respect to classical survey-based analyses, as they are quite expensive and may require up to one year before being available. In this paper we discuss how Web job vacancies have been collected from selected websites, processed, and classified over a standard taxonomy through machine learning algorithms, extracting the most relevant skills from raw texts. Then, we show how our approach has been applied to some real-life studies and we discuss the benefits provided to end users.

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تاریخ انتشار 2017