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Incorporating Domain Knowledge and User Expertise in Probabilistic Tuple Merging

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Scalable Uncertainty Management (SUM 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6929))

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Abstract

Today, probabilistic databases (PDB) become helpful in several application areas. In the context of cleaning a single PDB or integrating multiple PDBs, duplicate tuples need to be merged. A basic approach for merging probabilistic tuples is simply to build the union of their sets of possible instances. In a merging process, however, often additional domain knowledge or user expertise is available. For that reason, in this paper we extend the basic approach with aggregation functions, knowledge rules, and instance weights for incorporating external knowledge in the merging process.

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Author information

Authors and Affiliations

  1. Universität Hamburg, Vogt-Kölln Straße 33, 22527, Hamburg, Germany

    Fabian Panse & Norbert Ritter

Authors
  1. Fabian Panse
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  2. Norbert Ritter
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Editor information

Editors and Affiliations

  1. CRIL-CNRS, University of Artois, 62307, France

    Salem Benferhat

  2. Department of Mathematics, Towson University, 21252, Towson, MD, USA

    John Grant

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© 2011 Springer-Verlag Berlin Heidelberg

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Panse, F., Ritter, N. (2011). Incorporating Domain Knowledge and User Expertise in Probabilistic Tuple Merging. In: Benferhat, S., Grant, J. (eds) Scalable Uncertainty Management. SUM 2011. Lecture Notes in Computer Science(), vol 6929. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23963-2_23

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  • DOI: https://doi.org/10.1007/978-3-642-23963-2_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23962-5

  • Online ISBN: 978-3-642-23963-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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