The evaluation of matching applications is becoming a major issue in the semantic web and it requires a suitable methodological approach as well as appropriate benchmarks. In particular, in order to evaluate a matching application under different experimental conditions, it is crucial to provide a test dataset characterized by a controlled variety of different heterogeneities among data that rarely occurs in real data repositories. In this paper, we propose SWING (Semantic Web INstance Generation), a disciplined approach to the semi-automatic generation of benchmarks to be used for the evaluation of matching applications.
Benchmarking matching applications on the semantic Web / A. Ferrara, S. Montanelli, J. Noessner, H. Stuckenschmidt - In: The Semantic Web: Research and Applications / [a cura di] G. Antoniou, M. Grobelnik, E. Simperl, B. Parsia, D. Plexousakis, P. De Leenheer, J. Pan. - Berlin : Springer, 2011. - ISBN 9783642210631. - pp. 108-122 (( Intervento presentato al 8. convegno Extended Semantic Web Conference tenutosi a Heraklion nel 2011.
Benchmarking matching applications on the semantic Web
A. FerraraPrimo
;S. MontanelliSecondo
;
2011
Abstract
The evaluation of matching applications is becoming a major issue in the semantic web and it requires a suitable methodological approach as well as appropriate benchmarks. In particular, in order to evaluate a matching application under different experimental conditions, it is crucial to provide a test dataset characterized by a controlled variety of different heterogeneities among data that rarely occurs in real data repositories. In this paper, we propose SWING (Semantic Web INstance Generation), a disciplined approach to the semi-automatic generation of benchmarks to be used for the evaluation of matching applications.File | Dimensione | Formato | |
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