Goal of this paper is to propose a reference modeling framework to explicitly identify and formalize the different levels of variability that can arise along all the involved dimensions of a matching execution. The proposed framework is based on the notion of knowledge chunk, context, and mapping to abstract the variability levels and related operations along the source-dataset, the matching-dataset, and the mapping-set dimensions, respectively. An application of the proposed framework with instantiation in the HMatch 2.0 systems is illustrated. © Springer-Verlag Berlin Heidelberg 2010.
CITATION STYLE
Castano, S., Ferrara, A., & Montanelli, S. (2010). Dealing with matching variability of semantic web data using contexts. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6051 LNCS, pp. 194–208). https://doi.org/10.1007/978-3-642-13094-6_16
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