Name
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. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-04125-9_50 | ISMIS |
Keywords | Field | DocType |
semantic similarity,knowledge-based system,domain ontology,system performance,semantic technology,competence management,requested profile,semantic-based top-k retrieval,semantic-based ranking,reasoning service,top-k retrieval technique,knowledge based system,semantic technologies | Semantic similarity,Data mining,Talent management,Ontology,Conjunctive query,Semantic technology,Relational database,Information retrieval,Ranking,Computer science,Description logic | Conference |
Volume | ISSN | Citations |
5722 | 0302-9743 | 1 |
PageRank | References | Authors |
0.35 | 18 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Umberto Straccia | 1 | 2731 | 251.15 |
| Eufemia Tinelli | 2 | 90 | 11.70 |
| Simona Colucci | 3 | 1047 | 71.96 |
| Tommaso Di Noia | 4 | 1857 | 152.07 |
| Eugenio Sciascio | 5 | 25 | 3.02 |