Even though a few architectures exist to support the difficult ontology matching task, it happens often they are not reconfigurable (or just a little) related to both ontology features and applications needs. We introduce GENOMA, an architecture supporting development of Ontolo-gy Matching (OM) tools with the aims to reuse, possibly, existing modules each of them dealing with a specific task/subtasks of the OM process. In GENOMA flexibility and extendibility are considered mandatory features along with the ability to parallelize and distribute the processing load on dif-ferent systems. Thanks to a dedicated graphical user interface, GENOMA can be used by expert users, as well as novice, that can validate the resulting architecture. We highlight as main features of developed architecture: • to select, combine and set different parameters • to evaluate the matching tool applied to big size ontologies • efficiency of the OM tool • automatic balancing of the processing load on different systems

Enea, R., Pazienza, M.t., Turbati, A. (2015). GENOMA: GENeric Ontology Matching Architecture. In AI*IA 2015, Advances in Artificial Intelligence (pp. 303-315). Springer-Verlag [10.1007/978-3-319-24309-2_23].

GENOMA: GENeric Ontology Matching Architecture

PAZIENZA, MARIA TERESA;TURBATI, ANDREA
2015-01-01

Abstract

Even though a few architectures exist to support the difficult ontology matching task, it happens often they are not reconfigurable (or just a little) related to both ontology features and applications needs. We introduce GENOMA, an architecture supporting development of Ontolo-gy Matching (OM) tools with the aims to reuse, possibly, existing modules each of them dealing with a specific task/subtasks of the OM process. In GENOMA flexibility and extendibility are considered mandatory features along with the ability to parallelize and distribute the processing load on dif-ferent systems. Thanks to a dedicated graphical user interface, GENOMA can be used by expert users, as well as novice, that can validate the resulting architecture. We highlight as main features of developed architecture: • to select, combine and set different parameters • to evaluate the matching tool applied to big size ontologies • efficiency of the OM tool • automatic balancing of the processing load on different systems
2015
Settore ING-INF/05 - SISTEMI DI ELABORAZIONE DELLE INFORMAZIONI
English
Rilevanza internazionale
Capitolo o saggio
ontology matching; evaluation; architecture
SemaGrow is partially funded by the Seventh Framework Programme (FP7) of the European Commision (FP7-ICT-2011.4.4a Intelligent Information Management) under Grant Agreement No. 318497
Enea, R., Pazienza, M.t., Turbati, A. (2015). GENOMA: GENeric Ontology Matching Architecture. In AI*IA 2015, Advances in Artificial Intelligence (pp. 303-315). Springer-Verlag [10.1007/978-3-319-24309-2_23].
Enea, R; Pazienza, Mt; Turbati, A
Contributo in libro
File in questo prodotto:
File Dimensione Formato  
AIxIA_GENOMA GENeric Ontology Matching Architecture.pdf

solo utenti autorizzati

Descrizione: Articolo principale
Licenza: Copyright dell'editore
Dimensione 579.6 kB
Formato Adobe PDF
579.6 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/116462
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 4
  • ???jsp.display-item.citation.isi??? 1
social impact