Benchmarking matching applications on the semantic Web

Authors:
Alfio Ferrara;Stefano Montanelli;Jan Noessner;Heiner Stuckenschmidt
Affiliations:
Università degli Studi di Milano, Milano, Italy;Università degli Studi di Milano, Milano, Italy;KR & KM Research Group, University of Mannheim, Mannheim, Germany;KR & KM Research Group, University of Mannheim, Mannheim, Germany
Venue:
ESWC'11 Proceedings of the 8th extended semantic web conference on The semanic web: research and applications - Volume Part II
Year:
2011

Citing 8
Cited 3

The XOO7 Benchmark

Proceedings of the VLDB 2002 Workshop EEXTT and CAiSE 2002 Workshop DTWeb on Efficiency and Effectiveness of XML Tools and Techniques and Data Integration over the Web-Revised Papers
Ontology Matching

Ontology Matching
XBenchMatch: a benchmark for XML schema matching tools

VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Freebase: a collaboratively created graph database for structuring human knowledge

Proceedings of the 2008 ACM SIGMOD international conference on Management of data
STBenchmark: towards a benchmark for mapping systems

Proceedings of the VLDB Endowment
Evaluation of entity resolution approaches on real-world match problems

Proceedings of the VLDB Endowment
Matching ontologies in open networked systems: techniques and applications

Journal on Data Semantics V
Leveraging terminological structure for object reconciliation

ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part II

Probabilistic-logical web data integration

RW'11 Proceedings of the 7th international conference on Reasoning web: semantic technologies for the web of data
Evaluation of instance matching tools: The experience of OAEI

Web Semantics: Science, Services and Agents on the World Wide Web
Ontology matching benchmarks: Generation, stability, and discriminability

Web Semantics: Science, Services and Agents on the World Wide Web

Quantified Score

Hi-index	0.00

Visualization

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.