Semantics-aware matching strategy (SAMS) for the Ontology meDiated Data Integration (ODDI)
Marcello Leida, Paolo Ceravolo, Ernesto Damiani, Zhan Cui, Alex Gusmini · International Journal of Knowledge Engineering and Soft Data Paradigms · 2009
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.