@techreport{TD:100948,
	att_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.}},
	att_authors={ds8961, bs621s, pk1785, hk1971},
	att_categories={C_NSS.2, C_IIS.6},
	att_copyright={{IEEE}},
	att_copyright_notice={{This version of the work is reprinted here with permission of IEEE for your personal use. Not for redistribution. The definitive version was published in 2012. {{, Volume 26}}{{, Issue 6}}{{, 2014-06-01}}{{, http://doi.ieeecomputersociety.org/10.1109/TKDE.2012.171}}
}},
	att_donotupload={},
	att_private={false},
	att_projects={},
	att_tags={},
	att_techdoc={true},
	att_techdoc_key={TD:100948},
	att_url={http://web1.research.att.com:81/techdocs_downloads/TD:100948_DS1_2012-08-03T22:34:22.748Z.pdf},
	author={Divesh Srivastava and Barna Saha and Philip Korn and Howard Karloff and Lukasz Golab, University of Waterloo},
	institution={{IEEE Transactions on Knowledge and Data Engineering}},
	month={June},
	title={{Discovering Conservation Rules}},
	year=2014,
}