Large knowledge collider: a service-oriented platform for large-scale semantic reasoning

  • Authors:

  • Matthias Assel;Alexey Cheptsov;Georgina Gallizo;Irene Celino;Daniele Dell'Aglio;Luka Bradeško;Michael Witbrock;Emanuele Della Valle

  • Affiliations:

  • High Performance Computing Center Stuttgart, Nobelstr, Stuttgart (Germany);High Performance Computing Center Stuttgart, Nobelstr, Stuttgart (Germany);High Performance Computing Center Stuttgart, Nobelstr, Stuttgart (Germany);CEFRIEL - ICT Institute, Politecnico di Milano, Via Fucini, Milano (Italy);CEFRIEL - ICT Institute, Politecnico di Milano, Via Fucini, Milano (Italy);Cycorp Europe, Teslova Cesta, Ljubljana, Slovenia;Cycorp Europe, Teslova Cesta, Ljubljana, Slovenia;DEI -- Politecnico di Milano, Piazza Leonardo da Vinci, Milano (Italy)

  • Venue:
  • Proceedings of the International Conference on Web Intelligence, Mining and Semantics
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

Recent advances in the Semantic Web community have yielded a variety of reasoning methods used to process and exploit semantically annotated data. However, most of those methods have only been approved for small, closed, trustworthy, consistent, and static domains. Still, there is a deep mismatch between the requirements for reasoning on a Web scale and the existing efficient reasoning algorithms over restricted subsets. This paper describes the pilot implementation of LarKC -- the Large Knowledge Collider, a platform, which focuses on supporting large-scale reasoning over billions of structured data in heterogeneous data sets. The architecture of LarKC allows for an effective combination of techniques coming from different Semantic Web domains by following a service-oriented approach, supplied by sustainable infrastructure solutions.