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
Semantic-Based Top-k Retrieval for Competence Management / Straccia, U.; Tinelli, E.; Colucci, Simona; DI NOIA, Tommaso; DI SCIASCIO, Eugenio (LECTURE NOTES IN COMPUTER SCIENCE). - In: Foundations of intelligent systems: 18th International Symposium, ISMIS 2009, Prague, Czech Republic, September 14-17, 2009, proceedingsBerlin, Heidelberg : Springer, 2009. - ISBN 978-3-642-04124-2. - pp. 473-482 [10.1007/978-3-642-04125-9_50]
Semantic-Based Top-k Retrieval for Competence Management
COLUCCI, Simona;DI NOIA, Tommaso;DI SCIASCIO, Eugenio
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 resultsI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
