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RDF Ontology (Re-)Engineering through Large-scale Data Mining
| Citations: | 2 - 0 self |
BibTeX
@MISC{Lorey_rdfontology,
author = {Johannes Lorey and Ziawasch Abedjan and Felix Naumann},
title = {RDF Ontology (Re-)Engineering through Large-scale Data Mining},
year = {}
}
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Abstract
Abstract. As Linked Open Data originates from various sources, lever-aging well-defined ontologies aids integration. However, oftentimes the utilization of RDF vocabularies by data publishers differs from the in-tended application envisioned by ontology engineers. Especially in large-scale datasets as presented in the Billion Triple Challenge a significant divergence between vocabulary specification and usage patterns can be observed. This may impede the goals of the Web of Data in terms of dis-covering domain-specific information in the Semantic Web. In this work, we identify common misusage patterns by employing frequency analysis and rule mining and propose reengineering suggestions. 1
Keyphrases
large-scale data mining rdf ontology in-tended application open data originates ontology engineer significant divergence lever-aging well-defined ontology aid integration frequency analysis large-scale datasets rule mining usage pattern dis-covering domain-specific information semantic web vocabulary specification various source common misusage pattern billion triple challenge propose reengineering suggestion data publisher differs rdf vocabulary
