ReConRank: A Scalable Ranking Method for Semantic Web Data with Context
Aidan Hogan, Andreas Harth, Stefan Decker · Arrow@dit (Dublin Institute of Technology) · 2006
We present an approach that adapts the well-known PageRank/HITS algorithms to Semantic Web data. Our method combines ranks from the RDF graph with ranks from the context graph, i.e. data sources and their linkage. We present performance evaluation results based on a large RDF data set obtained from the Web.