We present a knowledge-based system, for skills and talent management, exploiting semantic technologies combined with top-k retrieval techniques. The system provides advanced distinguishing features, including the possibility to formulate queries by expressing both strict requirements and preferences in the requested profile and a semantic-based ranking of retrieved candidates. Based on the knowledge formalized within a domain ontology, the system implements an approach exploiting top-k based reasoning services to evaluate semantic similarity between the requested profile and retrieved ones. System performance is discussed through the presentation of experimental results.
Top-k retrieval for automated human resource management / Straccia, Umberto; Tinelli, Eufemia; Di Noia, Tommaso; Di Sciascio, Eugenio; Colucci, Simona. - (2009), pp. 161-168. (Intervento presentato al convegno 17th Italian Symposium on Advanced Database Systems, SEBD 2009 tenutosi a Camogli, Italy nel June 21-24, 2009).
Top-k retrieval for automated human resource management
Di Noia, Tommaso;Di Sciascio, Eugenio;Colucci, Simona
2009-01-01
Abstract
We present a knowledge-based system, for skills and talent management, exploiting semantic technologies combined with top-k retrieval techniques. The system provides advanced distinguishing features, including the possibility to formulate queries by expressing both strict requirements and preferences in the requested profile and a semantic-based ranking of retrieved candidates. Based on the knowledge formalized within a domain ontology, the system implements an approach exploiting top-k based reasoning services to evaluate semantic similarity between the requested profile and retrieved ones. System performance is discussed through the presentation of experimental results.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
