Difference between revisions of "Property Alignment"
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| − | = | + | ===Property Alignment on Linked Datasets=== |
| − | + | Property alignment in Linked Open Data (LOD) or linked datasets is a non-trivial task because of the complex data representations. Concept (class) and instance level alignment possibilities have been investigated in the recent past but property alignment has not received much attention yet. Therefore, we propose an approach that can handle complex data representations and also achieve higher correct matching ratio. Our approach is based on utilizing fundamental building block of the interlinked datasets (e.g., LOD) which is known as Entity Co-Reference (ECR) links. We try to match property extensions to come up with a measurement to approximate owl:equivalent property. We use ECR links to findout equivalent instances for a particular property extension and then accumulate the matching number of extensions to decide on a matching property pair between two datasets. | |
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| + | ==Approach== | ||
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| + | ==Experiment and Datasets== | ||
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| + | ==Analysis== | ||
Revision as of 00:44, 6 June 2013
Property Alignment on Linked Datasets
Property alignment in Linked Open Data (LOD) or linked datasets is a non-trivial task because of the complex data representations. Concept (class) and instance level alignment possibilities have been investigated in the recent past but property alignment has not received much attention yet. Therefore, we propose an approach that can handle complex data representations and also achieve higher correct matching ratio. Our approach is based on utilizing fundamental building block of the interlinked datasets (e.g., LOD) which is known as Entity Co-Reference (ECR) links. We try to match property extensions to come up with a measurement to approximate owl:equivalent property. We use ECR links to findout equivalent instances for a particular property extension and then accumulate the matching number of extensions to decide on a matching property pair between two datasets.
