Knowledge Based Open Entity Matching

TL;DRAbstract

In this work we argue for the definition a knowledge-based entity matching framework for the implementation of a reliable and incrementally scalable solution. Such knowledge base is formed by an ontology and a set of entity matching rules suitable to be applied as a reliable equational theory in the context of the Semantic Web. In particular, we are going to prove that relying on the existence of a set of contextual mappings to ease the semantic heterogeneity characterizing descriptions on the Web, a knowledge-based solution can perform comparably, and sometimes better, than existing solutions at the state of the art. We further argue that a knowledge-based solution to the open entity matching problem ought to be considered under the open world assumption, as in some cases the descriptions to be matched may not contain the necessary information to take any accurate matching decision. The main goal of this work is to show how the framework proposed is suitable to pursue a reliable solut

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