Determining Semantic Similarity among Entity Classes from Different Ontologies
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The paper proposes a method for query approximation in Geographic Information Systems. In particular, the problem of matching a query with imprecise or missing data is analyzed and an approach for the relaxation of query constraints is proposed. Query approximation is performed by relaxing structural constraints, according to an extension of a previous proposal for evaluating concept similarity in an ontology management system [1] inspired by the maximum weighted matching problem in bipartite graphs. In our approach, we start from a weighted hierarchy of geographical objects evaluated using WordNet, a lexical database for the English language available on the Internet. If a concept contained in a query has no match in the database, the query is approximated using a structural similarity graph that connects all geographical concepts by the lowest structural distance. The aim of the proposed methodology is to relax structural query constraints, in order to obtain meaningful answers for imprecise or missing data.