Semantic-Based Top-k Retrieval for Competence Management

Authors:
Umberto Straccia;Eufemia Tinelli;Simona Colucci;Tommaso Noia;Eugenio Sciascio
Affiliations:
ISTI-CNR, Pisa, Italy I-56124;SisInfLab-Politecnico of Bari, Bari, Italy 70125;SisInfLab-Politecnico of Bari, Bari, Italy 70125;SisInfLab-Politecnico of Bari, Bari, Italy 70125;SisInfLab-Politecnico of Bari, Bari, Italy 70125
Venue:
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
Year:
2009

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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.