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2012 IEEE 28th International Conference on Data Engineering
Discovering Conservation Rules
Arlington, Virginia USA
April 01-April 05
ISBN: 978-0-7695-4747-3
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.
Citation:
Lukasz Golab, Howard Karloff, Flip Korn, Barna Saha, Divesh Srivastava, "Discovering Conservation Rules," icde, pp.738-749, 2012 IEEE 28th International Conference on Data Engineering, 2012
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