PageRank and Generic Entity Summarization for RDF Knowledge Bases

Dennis Diefenbach (1) , Andreas Thalhammer

1 LHC - Laboratoire Hubert Curien

Ranking and entity summarization are operations that are tightly connected and recurrent in many different domains. Possible application fields include information retrieval, question answering, named entity disambiguation, co-reference resolution, and natural language generation. Still, the use of these techniques is limited because there are few accessible resources. PageRank computations are resource-intensive and entity summarization is a complex research field in itself. We present two generic and highly re-usable resources for RDF knowledge bases: a component for PageRank-based ranking and a component for entity summarization. The two components, namely PageRankRDF and summaServer, are provided in form of open source code along with example datasets and deployments. In addition, this work outlines the application of the components for PageRank-based RDF ranking and entity summarization in the question answering project WDAqua.

Mots clés: RDF; ranking; PageRank; entity summarization; question answering; linked data

Domaines: Informatique

Dennis Diefenbach, Andreas Thalhammer. PageRank and Generic Entity Summarization for RDF Knowledge Bases. European Semantic Web Conference ESWC 2018,, Jun 2018, Heraklion, Greece. ⟨hal-01905724⟩