Linked Data Annotation and Fusion driven by Data Quality Evaluation
Abstract
In this work, we are interested in exploring the problem of \emph{data fusion}, starting from reconciled datasets whose objects are linked with semantic sameAs relations. We attempt to merge the often conflicting information of these reconciled objects in order to obtain unified representations that only contain the best quality information.
Domains
Artificial Intelligence [cs.AI]Origin | Files produced by the author(s) |
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