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2013 IEEE 29th International Conference on Data Engineering (ICDE) (2012)
Arlington, Virginia USA
Apr. 1, 2012 to Apr. 5, 2012
ISSN: 1084-4627
ISBN: 978-0-7695-4747-3
pp: 738-749
ABSTRACT
Many applications process data in which there exists a ``conservation law'' between related quantities. For example, in traffic monitoring, every incoming event, such as a packet's entering a router or a car's entering an intersection, should ideally have an immediate outgoing counterpart. We propose a new class of constraints -- Conservation Rules -- that express the semantics and characterize the data quality of such applications. We give confidence metrics that quantify how strongly a conservation rule holds and present approximation algorithms (with error guarantees) for the problem of discovering a concise summary of subsets of the data that satisfy a given conservation rule. Using real data, we demonstrate the utility of conservation rules and we show order-of-magnitude performance improvements of our discovery algorithms over naive approaches.
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CITATION
Barna Saha, Flip Korn, Howard Karloff, Divesh Srivastava, Lukasz Golab, "Discovering Conservation Rules", 2013 IEEE 29th International Conference on Data Engineering (ICDE), vol. 00, no. , pp. 738-749, 2012, doi:10.1109/ICDE.2012.105
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