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The «VADORE» project

The «VADORE» project

  • The project
  • Contacts
AI to improve the job market: new functionalities available for job seekers and job providers.
The project
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Data Valuation for Job Search 

Unemployment is a multi-cause phenomenon, depending in particular on the factors limiting the offer and the demand for work. This project focuses on frictional unemployment, linked to informational imperfections, due to the costs of collecting, processing and diffusing information, as well as to the asymmetry of information between job offers and job seekers, and to the cognitive limitations of individuals. These imperfections are one of the reasons why some positions remain unoccupied even though there is a significant demand for jobs in the same employment sector.


The central idea of the project is to mobilize all available information to improve the matching of job seekers and job vacancies.


The project is based on the mobilization of the considerable body of information on job seekers and firms, some of which (notably textual data) is still untapped. This information will be used to develop, rigorously evaluate and compare two different functionalities, of different technical and economic inspiration.

The first functionality consists on issuing formalized recommendations to both job seekers (about the companies to apply to) and companies (about the job seekers to invite for recruitment interviews) using previous work (Schmitt et al., 2016, 2017).

The second functionality consists on making available to job seekers and companies an interactive map of employment, allowing them to view in an aggregated way job offers and job applications in a geographical area and responding to a given request.

The originality of this functionality is to allow users to access the global landscape according to their query - and to see how the landscape changes according to the eventual modifications of the query, allowing them to make not only choices but also requests in a more informed way.


Jobs space visualization with Cartolabe