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Australasian Database Conference

ADC 2016: Databases Theory and Applications pp 179–190Cite as

Integration of Probabilistic Information

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9877))

Abstract

We study the problem of data integration from sources that contain probabilistic uncertain information. Data is modeled by possible-worlds with probability distribution, compactly represented in the probabilistic relation model. Integration is achieved efficiently using the extended probabilistic relation model. We study the problem of determining the probability distribution of the integration result. It has been shown that, in general, only probability ranges can be determined for the result of integration. We show that under intuitive and reasonable assumptions we can determine the exact probability distribution of the result of integration. Our methodologies are presented in possible-worlds as well as probabilistic-relation frameworks.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of North Carolina, Greensboro, NC, USA

    Fereidoon Sadri & Gayatri Tallur

Authors
  1. Fereidoon Sadri
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  2. Gayatri Tallur
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Corresponding author

Correspondence to Fereidoon Sadri .

Editor information

Editors and Affiliations

  1. Monash University , Clayton, Australia

    Muhammad Aamir Cheema

  2. School of Comp. Science a. Engineer, University of New South Wales School of Comp. Science a. Engineer, Sydney, Australia

    Wenjie Zhang

  3. University of New South Wales , Sydney, New South Wales, Australia

    Lijun Chang

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© 2016 Springer International Publishing AG

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Sadri, F., Tallur, G. (2016). Integration of Probabilistic Information. In: Cheema, M., Zhang, W., Chang, L. (eds) Databases Theory and Applications. ADC 2016. Lecture Notes in Computer Science(), vol 9877. Springer, Cham. https://doi.org/10.1007/978-3-319-46922-5_14

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  • DOI: https://doi.org/10.1007/978-3-319-46922-5_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46921-8

  • Online ISBN: 978-3-319-46922-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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