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2007

Detecting Quality Problems in Semantic Metadata without the Presence of a Gold Standard

8 years 8 months ago
Detecting Quality Problems in Semantic Metadata without the Presence of a Gold Standard
Detecting quality problems in semantic metadata is crucial for ensuring a high quality semantic web. Current approaches are primarily focused on the algorithms used in semantic metadata generation rather than on the data themselves. They typically require the presence of a gold standard and are not suitable for assessing the quality of semantic metadata. This paper proposes a novel approach, which exploits a range of knowledge sources including both domain and background knowledge to support semantic metadata evaluation without the need of a gold standard. We have conducted a set of preliminary experiments, which show promising results.
Yuangui Lei, Andriy Nikolov
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where EON
Authors Yuangui Lei, Andriy Nikolov
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