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RdfRules Preview: Towards an Analytics Engine for Rule Mining in RDF Knowledge Graphs

EasyChair Preprint no. 478

14 pagesDate: August 31, 2018

Abstract

RdfRules is a framework for mining logical rules from RDF-style knowledge graphs. The system provides software support for the complete data mining workflows over RDF data: data ingestion, aggregation, transformations, actual rule mining and post-processing of discovered rules, including clustering. As a rule mining algorithm, RdfRules adopts AMIE+ (Galárraga et al, 2015), which has been extended with number of practical features, such as mining across multiple graphs, top-\textit{k} approach and the ability to define fine-grained patterns to reduce the size of the search space. RdfRules is a work-in-progress.

Keyphrases: knowledge bases, RDF data analysis, Rule Mining, Semantic Web Tool

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:478,
  author = {Václav Zeman and Tomáš Kliegr and Vojtěch Svátek},
  title = {RdfRules Preview: Towards an Analytics Engine for Rule Mining in RDF Knowledge Graphs},
  howpublished = {EasyChair Preprint no. 478},
  doi = {10.29007/nkv7},
  year = {EasyChair, 2018}}
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