How Service Choreography Statistics Reduce the Ontology Mapping Problem

In open and distributed environments ontology mapping provides interoperability between interacting actors. However, conventional mapping systems focus on acquiring static information, and on mapping whole ontologies, which is infeasible in open systems. This paper shows that the interactions themselves between the actors can be used to predict mappings, simplifying dynamic ontology mapping. The intuitive idea is that similar interactions follow similar conventions and patterns, which can be analysed. The computed model can be used to suggest the possible mappings for the exchanged messages in new interactions. The suggestions can be evaluate by any standard ontology matcher: if they are accurate, the matchers avoid evaluating mappings unrelated to the interaction.

The minimal requirement in order to use this system is that it is possible to describe and identify the interaction sequences: the OpenKnowledge project has produced an implementation that demonstrates this is possible in a fully peer-to-peer environment.