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.
A system for retrieving top-k candidates to job positions
Straccia U;
2009
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.File | Dimensione | Formato | |
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Descrizione: A system for retrieving top-k candidates to job positions
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