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dc.contributor.authorMiranda, S.
dc.contributor.authorOrciuoli, F.
dc.contributor.authorLoia, V.
dc.contributor.authorSampson, Demetrios
dc.date.accessioned2017-03-17T08:29:41Z
dc.date.available2017-03-17T08:29:41Z
dc.date.created2017-02-19T19:31:39Z
dc.date.issued2017
dc.identifier.citationMiranda, S. and Orciuoli, F. and Loia, V. and Sampson, D. 2017. An ontology-based model for competence management. Data and Knowledge Engineering. 107: pp. 51-66.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/51103
dc.identifier.doi10.1016/j.datak.2016.12.001
dc.description.abstract

© 2017 Elsevier B.V.In the last years, the need for developing strategies, models and tools to manage competences clearly emerges in numerous scenarios. For instance, this emergence especially raises when it is required to realize effective recruiting platforms, decision support systems for human resource management, learning management systems and so on. This work proposes an ontology-based model for the representation of competences able to support a wide range of scenarios where it is fundamental to model, organize and represent professional competences, enable interoperability and co-operation among different and heterogeneous tools and, lastly, execute queries and inference operations over these competences. The proposed model starts from the outcomes of the specialized literature and the related R&D projects and produces a novel integrated model that represents both job offers and demands to support recruiting initiatives and to develop employability strategies aiming at a best matching as well as a careful skill gap analysis. The model has been evaluated by means of a three-level approach also in the context of the SIRET project whose goal is defining a recruiting and training integrated system able to represent the professional competences of users and to understand the supplies and the demands in order to find optimal agreements in the job market.

dc.publisherElsevier Science
dc.titleAn ontology-based model for competence management
dc.typeJournal Article
dcterms.source.volume107
dcterms.source.startPage51
dcterms.source.endPage66
dcterms.source.issn0169-023X
dcterms.source.titleData and Knowledge Engineering
curtin.departmentSchool of Education
curtin.accessStatusFulltext not available


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