Querying Factorized Probabilistic Triple Databases

  • Denis Krompaß
  • Maximilian Nickel
  • Volker Tresp
Conference paper

DOI: 10.1007/978-3-319-11915-1_8

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8797)
Cite this paper as:
Krompaß D., Nickel M., Tresp V. (2014) Querying Factorized Probabilistic Triple Databases. In: Mika P. et al. (eds) The Semantic Web – ISWC 2014. ISWC 2014. Lecture Notes in Computer Science, vol 8797. Springer, Cham

Abstract

An increasing amount of data is becoming available in the form of large triple stores, with the Semantic Web’s linked open data cloud (LOD) as one of the most prominent examples. Data quality and completeness are key issues in many community-generated data stores, like LOD, which motivates probabilistic and statistical approaches to data representation, reasoning and querying. In this paper we address the issue from the perspective of probabilistic databases, which account for uncertainty in the data via a probability distribution over all database instances. We obtain a highly compressed representation using the recently developed RESCAL approach and demonstrate experimentally that efficient querying can be obtained by exploiting inherent features of RESCAL via sub-query approximations of deterministic views.

Keywords

Probabilistic Databases Tensor Factorization RESCAL Querying Extensional Query Evaluation 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Denis Krompaß
    • 1
  • Maximilian Nickel
    • 2
    • 3
  • Volker Tresp
    • 1
    • 4
  1. 1.Ludwig Maximilian UniversityMunichGermany
  2. 2.Massachusetts Institute of TechnologyCambridgeUSA
  3. 3.Istituto Italiano di TecnologiaGenovaItaly
  4. 4.Siemens AG, Corporate TechnologyMunichGermany

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