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Probabilistic Inductive Querying Using ProbLog

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Inductive Databases and Constraint-Based Data Mining

Abstract

We study how probabilistic reasoning and inductive querying can be combined within ProbLog, a recent probabilistic extension of Prolog. ProbLog can be regarded as a database system that supports both probabilistic and inductive reasoning through a variety of querying mechanisms. After a short introduction to ProbLog, we provide a survey of the different types of inductive queries that ProbLog supports, and show how it can be applied to the mining of large biological networks.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Katholieke Universiteit Leuven, Leuven, Belgium

    Luc De Raedt, Angelika Kimmig & Bernd Gutmann

  2. Fraunhofer IAIS, Sankt Augustin, Germany

    Kristian Kersting

  3. Faculdade de Ciências, Universidade do Porto, Porto, Portugal

    Vítor Santos Costa

  4. Department of Computer Science, University of Helsinki, Helsinki, Finland

    Hannu Toivonen

Authors
  1. Luc De Raedt
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  2. Angelika Kimmig
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  3. Bernd Gutmann
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  4. Kristian Kersting
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  5. Vítor Santos Costa
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  6. Hannu Toivonen
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Corresponding author

Correspondence to Luc De Raedt .

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Editors and Affiliations

  1. , Department of Knowledge Technologies, Jozef Stefan Institute, Jamova 39, Ljubljana, 1000, Slovenia

    Sašo Džeroski

  2. , Mathematics and Computer Science, University of Antwerp, Middelheimlaan 1, Antwerpen, B-2020, Belgium

    Bart Goethals

  3. , Dept. of Knowledge Technologies, Jožef Stefan Institute, Jamova cesta 39, Ljubljana, SI-1000, Slovenia

    Panče Panov

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De Raedt, L., Kimmig, A., Gutmann, B., Kersting, K., Costa, V., Toivonen, H. (2010). Probabilistic Inductive Querying Using ProbLog. In: Džeroski, S., Goethals, B., Panov, P. (eds) Inductive Databases and Constraint-Based Data Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-7738-0_10

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  • DOI: https://doi.org/10.1007/978-1-4419-7738-0_10

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