Inference Optimization using Relational Algebra

S. Evers, M.M. Fokkinga, Peter M.G. Apers

Research output: Book/ReportReportProfessional

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Abstract

Exact inference procedures in Bayesian networks can be expressed using relational algebra; this provides a common ground for optimizations from the AI and database communities. Specifically, the ability to accomodate sparse representations of probability distributions opens up the way to optimize for their cardinality instead of the dimensionality; we apply this in a sensor data model.
Original languageUndefined
Place of PublicationEnschede
PublisherDatabases (DB)
Number of pages13
Publication statusPublished - Aug 2009

Publication series

NameCTIT Technical Report Series
PublisherCentre for Telematics and Information Technology, University of Twente
No.TR-CTIT-09-38
ISSN (Print)1381-3625

Keywords

  • Probabilistic inference
  • IR-68553
  • Bayesian Networks
  • EWI-16524
  • METIS-265240
  • Relational algebra
  • Sensor data

Cite this

Evers, S., Fokkinga, M. M., & Apers, P. M. G. (2009). Inference Optimization using Relational Algebra. (CTIT Technical Report Series; No. TR-CTIT-09-38). Enschede: Databases (DB).
Evers, S. ; Fokkinga, M.M. ; Apers, Peter M.G. / Inference Optimization using Relational Algebra. Enschede : Databases (DB), 2009. 13 p. (CTIT Technical Report Series; TR-CTIT-09-38).
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keywords = "Probabilistic inference, IR-68553, Bayesian Networks, EWI-16524, METIS-265240, Relational algebra, Sensor data",
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Evers, S, Fokkinga, MM & Apers, PMG 2009, Inference Optimization using Relational Algebra. CTIT Technical Report Series, no. TR-CTIT-09-38, Databases (DB), Enschede.

Inference Optimization using Relational Algebra. / Evers, S.; Fokkinga, M.M.; Apers, Peter M.G.

Enschede : Databases (DB), 2009. 13 p. (CTIT Technical Report Series; No. TR-CTIT-09-38).

Research output: Book/ReportReportProfessional

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AB - Exact inference procedures in Bayesian networks can be expressed using relational algebra; this provides a common ground for optimizations from the AI and database communities. Specifically, the ability to accomodate sparse representations of probability distributions opens up the way to optimize for their cardinality instead of the dimensionality; we apply this in a sensor data model.

KW - Probabilistic inference

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KW - Bayesian Networks

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KW - METIS-265240

KW - Relational algebra

KW - Sensor data

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Evers S, Fokkinga MM, Apers PMG. Inference Optimization using Relational Algebra. Enschede: Databases (DB), 2009. 13 p. (CTIT Technical Report Series; TR-CTIT-09-38).