Semantics-aware matching strategy (SAMS) for the Ontology meDiated Data Integration (ODDI)
by Marcello Leida, Paolo Ceravolo, Ernesto Damiani, Zhan Cui, Alex Gusmini
International Journal of Knowledge Engineering and Soft Data Paradigms (IJKESDP), Vol. 2, No. 1, 2010

Abstract: Data integration systems are used to integrate heterogeneous data sources in a single view. Recent work on business intelligence highlights the need of on-time, reliable and sound data access systems relying on methods based on semi-automatic procedures. A crucial factor for any semi-automatic algorithm is that of the matching strategy. Different categories of matching operators carry different semantics. For this reason, combining them into a single strategy is a non-trivial process that has to take into account a variety of options. This paper presents SAMS, a matching strategy based on a semantics-aware categorisation of matching operators that allows to group similar attributes on a semantically-rich form.

Online publication date: Thu, 17-Dec-2009

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