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Output details

11 - Computer Science and Informatics

University of Oxford

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Output 40 of 263 in the submission

Article title

Anytime approximation in probabilistic databases

Type

D - Journal article

DOI

10.1007/s00778-013-0310-5

Title of journal

VLDB Journal

Article number

Volume number

n/a

Issue number

First page of article

n/a

ISSN of journal

1066-8888

Year of publication

2013

URL

http://link.springer.com/article/10.1007/s00778-013-0310-5

Number of additional authors

Additional information

<15>

This article describes an approximation algorithm for computing the probability of propositional formulas over discrete random variables. It is used by the SPROUT query engine to approximate the probabilities of results to relational algebra queries on expressive probabilistic databases. It puts together research previously reported in International Conferences on Database Theory (ICDT 2011) and on Data Engineering (ICDE 2010 and 2011). Aspects of this work were used and extended for top-k by Olteanu (ICDE 2012) and Theobald (ICDE 2013), for aggregates by Fink (VLDB 2012), for XML by Senellart (ICDE 2013), for explanation and sensitivity analysis by Deshpande (SIGMOD 2011).

Interdisciplinary

Cross-referral requested

Research group

None

Citation count

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract