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DBpedia Domains: augmenting DBpedia with domain information

Gregor TitzeVolha BrylCäcilia ZirnSimone Paolo Ponzetto • @International Conference on Language Resources and Evaluation • 01 May 2014

TLDR: This work uses the thematic labels provided for DBpedia entities by Wikipedia categories, and groups them based on a kernel based k-means clustering algorithm, thus providing the largest LOD domain-annotated ontology to date.

Citations: 5
Abstract: We present an approach for augmenting DBpedia, a very large ontology lying at the heart of the Linked Open Data (LOD) cloud, with domain information. Our approach uses the thematic labels provided for DBpedia entities by Wikipedia categories, and groups them based on a kernel based k-means clustering algorithm. Experiments on gold-standard data show that our approach provides a first solution to the automatic annotation of DBpedia entities with domain labels, thus providing the largest LOD domain-annotated ontology to date.

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