A vector space model for automatic indexing
Communications of the ACM
The Knowledge Engineering Review
Constructing virtual documents for ontology matching
Proceedings of the 15th international conference on World Wide Web
The Knowledge Engineering Review
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In a Semantic-Web-like multi-agent environment, ontology mismatch is inevitable: we can't realistically expect agents created at different times and places by different people to commit to one unchanging universal ontology. Ontology matching seems to be the only solution to such a problem. However, standard techniques for aligning heterogeneous ontologies are based on time-consuming, off-line and often semi-automated processes and pre-suppose full access to the interacting agents' ontologies. This is far from ideal in situations where agents meet for the first time, interact quickly and have restricted access to other agents' private information. In this paper we present the Ontology Repair System (ORS), which attempts to match fully-fledged first-order ontologies automatically using incomplete information. Particular emphasis is laid on its semantic matching module, the Semantic Matcher, which provides a solution for lexical mismatches, which are the most common and the most challenging to address. ORS and the Semantic Matcher have been implemented and evaluated, with very promising results.