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.
Semantics-aware matching strategy (SAMS) for the ontology mediated data integration (ODDI) / M. Leida, P. Ceravolo, E. Damiani, Z. Cui, A. Gusmini. - In: INTERNATIONAL JOURNAL OF KNOWLEDGE ENGINEERING AND SOFT DATA PARADIGMS. - ISSN 1755-3210. - 2:1(2010), pp. 33-56. [10.1504/IJKESDP.2010.030465]
Semantics-aware matching strategy (SAMS) for the ontology mediated data integration (ODDI)
M. LeidaPrimo
;P. CeravoloSecondo
;E. Damiani;A. GusminiUltimo
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.Pubblicazioni consigliate
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