Bridging the Gap – An AI-enabled versatile skill matching tool to assist the less privileged

The job market is continuously evolving. The specific occupations, skills, competences and qualifications that people need change over time, as does their description. To deal with this, effective...

More specifically, in our proposal, we decompose the problem in the areas of: • searching for jobs and matching them with individual profiles (i.e. CVs), • searching for educational resources and matching them with individual profiles or job descriptions, in a layered approach, • skill building with the help of virtual assistants empowered by intelligent agents, used to the best of our knowledge first time under this domain, that will handle each participant as a unique case that should be supported and improved. This module will provide a personalised plan for skill-improvement (through open or low-cost educational activities) and job-finding (through providing motivation to employees and employers) even for the underprivileged young people in EU.

This proposal follows a bottom-up methodology investigating the problem of formalising the lifelong learning process in a dynamic and flexible way. On the other hand, this proposal utilises a parallel top-down approach in applying semantics and standards upon data in order to alleviate the gap among individuals, workplaces and educational contexts for the benefit of all in a transparent way.

Focusing on dissemination, deliverables, results and effects of this proposal, we summarise our intentions to provide: • tools to individuals to annotate CVs, manage their learning paths and offer people the possibility of compiling CVs and vacancies using ESCO’s vocabulary in all ESCO languages, enabling them to exchange information across borders. • tools to HR departments, job recruitment experts and other relevant stakeholders in order to best describe job vacancies, showing transparently how skills and competencies developed in one occupation are applicable and transferable to another one, i.e. cross-sectoral skills and competences. • tools to educational and HR experts to better describe formal qualifications to describe using web 2.0 techniques (e.g. recommendation-rating-reputation-badge systems) the not so formally acquired skills of individuals. • tools for the automated analysis, interpretation and matching of semi-structured and unstructured data (CVs and vacancies) and thus supporting competency-based job matching on the grounds of an individual’s work experience and qualifications. • recommendation machines providing fully automatic composite web-services or semi-automatic visualised services to EU citizens while building an e-portfolio for their lifelong learning and working progress within EU, • tools for intelligent analysis, recommendations and forecasts for curricula and courses to cover skills shortages required by the job market, • agent-based intelligent module that will analyse and support each individual participant in skill-building by providing virtual mentoring and long-life training dynamic and flexible plans.