Ranking RDF with Provenance via Preference Aggregation

  • Renata Dividino
  • Gerd Gröner
  • Stefan Scheglmann
  • Matthias Thimm
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7603)


Information retrieval on RDF data benefits greatly from additional provenance information attached to the individual pieces of information. Provenance information such as origin of data, certainty, and temporal information on RDF statements can be used to rank search results according to one of those dimensions. In this paper, we consider the problem of aggregating provenance information from different dimensions in order to obtain a joint ranking over all dimensions. We relate this to the problem of preference aggregation in social choice theory and translate different solutions for preference aggregation to the problem of aggregating provenance rankings. By exploiting the ranking orderings on the provenance dimensions, we characterize three different approaches for aggregating preferences, namely the lexicographical rule, the Borda rule and the plurality rule, in our framework of provenance aggregation.


Query Result Preference Aggregation Social Choice Theory Plurality Rule Judgement Aggregation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Renata Dividino
    • 1
  • Gerd Gröner
    • 1
  • Stefan Scheglmann
    • 1
  • Matthias Thimm
    • 1
  1. 1.Institute for Web Science and Technologies (WeST)University of Koblenz-LandauGermany

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