Paper Info
Title
Detecting Quality Problems in Semantic Metadata without the Presence of a Gold Standard
Abstract
Detecting quality problems in semantic metadata is crucial for ensuring a high quality semantic web. Current approaches are pri- marily 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 se- mantic 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.
Year
Venue
Keywords
2007
EON
gold standard,semantic web
Field
DocType
Citations 
Metadata,Metadata repository,Semantic technology,Information retrieval,Semantic Web Stack,Computer science,Semantic analytics,Semantic grid,Social Semantic Web,Semantic computing
Conference
5
PageRank 
References 
Authors
0.67
11
2
Name
Order
Citations
PageRank
Yuangui Lei126416.07
Andriy Nikolov276953.09