Meenakshi Rana
Department of Computer Science & Engineering, KEC Ghaziabad
Ashish Punya
Department of Computer Science & Engineering, KEC Ghaziabad
Download PDFOntology mapping is the key to data interoperability in the semantic web vision. Computing mappings is the first step to applications such as query rewriting, instance sharing, web-service integration, and ontology merging. This problem has received a lot of attention in recent years, but little is known about how users actually construct mappings. Several ontology-mapping tools have been developed, but which tools do users actually use? What processes are users following to discover, track, and compute mappings? How do teams coordinate when performing mappings? In this paper, we discuss the results from an online user survey where we gathered feedback from the community to help answer these important questions. We discuss the results from the survey and the implications they may have on the mapping research community. Most existing ontology mapping tools do not provide exact mappings. Rather, there is usually some degree of uncertainty. We describe a framework to improve existing ontology mappings using a Bayesian Network. Omen, an Ontology Mapping ENhancer uses a set of meta-rules that capture the influence of the ontology structure and the semantics of ontology relations and matches nodes that are neighbours of already matched nodes in the two ontologies. We have implemented a prototype ontology matcher that can enhance existing matches between ontology concepts. Preliminary experiments demonstrate that Omen successfully identifies and enhances ontology mappings.
Keywords: community; heterogeneous ; mappings ; neighbourhood
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