dc.contributor.author |
Roblot, Tania |
en |
dc.contributor.author |
Link, Sebastian |
en |
dc.contributor.editor |
Johannesson, P |
en |
dc.contributor.editor |
Lee, ML |
en |
dc.contributor.editor |
Liddle, SW |
en |
dc.contributor.editor |
Opdahl, AL |
en |
dc.contributor.editor |
Pastor Lopez, O |
en |
dc.coverage.spatial |
Stockholm, Sweden |
en |
dc.date.accessioned |
2016-08-21T23:21:21Z |
en |
dc.date.issued |
2015 |
en |
dc.identifier.citation |
Proceedings of the 34th International Conference on Conceptual Modeling, 2015, 9381 pp. 214 - 228 |
en |
dc.identifier.isbn |
978-3-319-25263-6 |
en |
dc.identifier.issn |
0302-9743 |
en |
dc.identifier.uri |
http://hdl.handle.net/2292/30081 |
en |
dc.description.abstract |
Probabilistic databases address well the requirements of an increasing number of modern applications that produce large collections of uncertain data. We propose probabilistic cardinality constraints as a principled tool for controlling the occurrences of data patterns in probabilistic databases. Our constraints help organizations balance their targets for different data quality dimensions, and infer probabilities on the number of query answers. These applications are unlocked by developing algorithms to reason efficiently about probabilistic cardinality constraints, and to help analysts acquire the marginal probability by which cardinality constraints hold in a given application domain. For this purpose, we overcome technical challenges to compute Armstrong PC-sketches as succinct data samples that perfectly visualize any given perceptions about these marginal probabilities. |
en |
dc.publisher |
Springer |
en |
dc.relation.ispartof |
ER 2015, 34th International Conference on Conceptual Modeling, |
en |
dc.relation.ispartofseries |
Lecture Notes on Computer Science: Conceptual Modeling 34th International Conference, ER 2015 |
en |
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. Details obtained from http://www.sherpa.ac.uk/romeo/issn/0302-9743/ |
en |
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
en |
dc.title |
Probabilistic Cardinality Constraints |
en |
dc.type |
Conference Item |
en |
dc.identifier.doi |
10.1007/978-3-319-25264-3_16 |
en |
pubs.begin-page |
214 |
en |
pubs.volume |
9381 |
en |
dc.description.version |
AM - Accepted Manuscript |
en |
dc.rights.holder |
Copyright:
Springer |
en |
pubs.end-page |
228 |
en |
pubs.finish-date |
2015-10-22 |
en |
pubs.publication-status |
Published |
en |
pubs.start-date |
2015-10-19 |
en |
dc.rights.accessrights |
http://purl.org/eprint/accessRights/OpenAccess |
en |
pubs.subtype |
Conference Paper |
en |
pubs.elements-id |
502991 |
en |
pubs.org-id |
Science |
en |
pubs.org-id |
School of Computer Science |
en |
dc.identifier.eissn |
1611-3349 |
en |
pubs.record-created-at-source-date |
2015-11-04 |
en |