Serving DBpedia with Dolce - More than Just Adding a Cherry on Top
- authors: @heiko-paulheim @aldo-gangemi
Abstract
Large knowledge bases, such as DBpedia, are most often cre- ated heuristically due to scalability issues. In the building process, both random as well as systematic errors may occur. In this paper, we focus on finding systematic errors, or anti-patterns, in DBpedia. We show that by aligning the DBpedia ontology to the foundational ontology DOLCE- Zero, and by combining reasoning and clustering of the reasoning results, errors affecting millions of statements can be identified at a minimal workload for the knowledge base designer.
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