Students and workers mobility in the European scenario represents today a big challenge. During the last years, several initiatives have been carried out to deal with the above picture, being the European Qualication Framework (EQF), a common architecture for describing qualications, one of the most signicant. In parallel, several research activities were established with the aim of exploiting semantic technologies for qualication comparison in the context of human resources acquisition. In this paper, the EQF specications are applied in a practical scenario to develop a ranking algorithm allowing for qualication comparison on the basis of knowledge, skill and competence concepts, potentially aimed at supporting European employers during the recruitment phases.
A semantic matchmaking system for job recruitment / Gatteschi, Valentina; Lamberti, Fabrizio; Sanna, Andrea; Demartini, Claudio Giovanni. - ELETTRONICO. - 1:(2010), pp. 50-59. (Intervento presentato al convegno 10th International Conference on Knowledge Management and Knowledge Technologies (I-KNOW2010) tenutosi a Graz (AT) nel 1-3 September, 2010).
A semantic matchmaking system for job recruitment
GATTESCHI, VALENTINA;LAMBERTI, FABRIZIO;SANNA, Andrea;DEMARTINI, Claudio Giovanni
2010
Abstract
Students and workers mobility in the European scenario represents today a big challenge. During the last years, several initiatives have been carried out to deal with the above picture, being the European Qualication Framework (EQF), a common architecture for describing qualications, one of the most signicant. In parallel, several research activities were established with the aim of exploiting semantic technologies for qualication comparison in the context of human resources acquisition. In this paper, the EQF specications are applied in a practical scenario to develop a ranking algorithm allowing for qualication comparison on the basis of knowledge, skill and competence concepts, potentially aimed at supporting European employers during the recruitment phases.Pubblicazioni consigliate
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https://hdl.handle.net/11583/2370817
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