dc.contributor.author |
Brown, P |
en |
dc.contributor.author |
Link, S |
en |
dc.date.accessioned |
2016-01-04T21:55:57Z |
en |
dc.date.available |
2016-01-04T21:55:57Z |
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dc.date.issued |
2015 |
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dc.identifier.citation |
CDMTCS Research Reports CDMTCS-483 (2015) |
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dc.identifier.issn |
1178-3540 |
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dc.identifier.uri |
http://hdl.handle.net/2292/27852 |
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dc.description.abstract |
Probabilistic databases address well the requirements of an increasing number of modern applications that produce large volumes of uncertain data from a variety of sources. We propose probabilistic keys as a principled tool helping organizations balance the consistency and completeness targets for their data quality. For this purpose, algorithms are established for an agile schema- and data-driven acquisition of the marginal probability by which keys should hold in a given application domain, and for reasoning about these keys. The efficiency of our acquisition framework is demonstrated theoretically and experimentally. |
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dc.publisher |
Department of Computer Science, The University of Auckland, New Zealand |
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dc.relation.ispartofseries |
CDMTCS Research Report Series |
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dc.rights |
Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. |
en |
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
en |
dc.source.uri |
https://www.cs.auckland.ac.nz/research/groups/CDMTCS/researchreports/index.php |
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dc.title |
Probabilistics Keys |
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dc.type |
Technical Report |
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dc.subject.marsden |
Fields of Research |
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dc.rights.holder |
The author(s) |
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dc.rights.accessrights |
http://purl.org/eprint/accessRights/OpenAccess |
en |