A mapping system for the integration of OWL-DL ontologies
Proceedings of the first international workshop on Interoperability of heterogeneous information systems
Processing Ontology Alignments with SPARQL
CISIS '08 Proceedings of the 2008 International Conference on Complex, Intelligent and Software Intensive Systems
LUBM: A benchmark for OWL knowledge base systems
Web Semantics: Science, Services and Agents on the World Wide Web
Ontology mapping and SPARQL rewriting for querying federated RDF data sources
OTM'10 Proceedings of the 2010 international conference on On the move to meaningful internet systems: Part II
JustBench: a framework for OWL benchmarking
ISWC'10 Proceedings of the 9th international semantic web conference on The semantic web - Volume Part I
Approaches to Relating and Integrating Semantic Data from Heterogeneous Sources
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
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Semantic technologies are increasingly being employed to integrate, relate and classify heterogeneous data from various problem domains. To date, however, little empirical analysis has been carried out to help identify the benefits and limitations of different semantic approaches on specific data integration and classification problems. This paper evaluates three alternative semantic techniques for performing classification over data derived from the telecommunications domain. The problem of interest involves inferring the "health" status of network nodes (femtocells) from synthesized performance management (PM) instance data based on the operational PM schema. The semantic approaches used in the comparison include OWL2 axioms, SPARQL queries and SWRL rules. Empirical tests were performed across a range of data set sizes, using Pellet for axioms and rules and ARQ for queries. The experimental results provide (mostly) quantitative and (some) qualitative indication of the relative merits of each approach. Key among these findings is confirmation of the clear superiority of queries over rules and axioms in terms of raw performance and scalability.