Abstract
Matching ontologies is a crucial process when facilitating system interoperability and information exchange. A reoccurring problem in this process is that names can be ambiguous, yielding uncertainty to whether entities of two heterogeneous ontologies are actually related. Linguistic ontologies provide a clear structure of meanings, rather than names, allowing the quantification of the relatedness of any two given meanings. We propose an approach for the automatic allocation of correct meanings within a linguistic ontology through the use of virtual documents and information retrieval techniques. The benefits of this approach are tested and established using a data set from the Ontology Alignment Evaluation Initiative (OAEI) competition, while further improvements are revealed using a benchmark data set from the same competition.
Original language | English |
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Title of host publication | Proceedings of the 23rd Belgian-Dutch Conference on Artificial Intelligence (BNAIC 2011) |
Place of Publication | Gent, Belgium |
Pages | 191-198 |
Number of pages | 8 |
Publication status | Published - 1 Nov 2011 |