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

EasyChair Preprint 478

14 pages•Date: August 31, 2018

Václav Zeman, Tomáš Kliegr and Vojtěch Svátek

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

Links:	https://easychair.org/publications/preprint/mJMw
	https://doi.org/10.29007/nkv7

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},
  doi       = {10.29007/nkv7},
  howpublished = {EasyChair Preprint 478},
  year      = {EasyChair, 2018}}

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