@techreport{TD:101707,
	att_abstract={{Entity resolution (ER) is the task of identifying all records in a database that refer to the same underlying entity. This is an expensive task, and can take a significant amount of money and time; the end-user may want to take decisions during the process, rather than waiting for the task to be completed. We formalize an online version of the entity resolution task, and use an oracle which correctly labels matching and non-matching pairs through queries. In this
setting, we design algorithms that seek to maximize progressive recall, and develop a novel analysis framework for prior proposals on entity resolution with an oracle, beyond their worst case guarantees. Finally, we provide both theoretical and experimental analysis of the proposed algorithms.}},
	att_authors={ds8961},
	att_categories={C_BB.1, C_NSS.2, C_IIS.5},
	att_copyright={{VLDB Foundation}},
	att_copyright_notice={{The definitive version was published in Very Large Databases, 2015. {{, Volume 9}}{{, Issue 5}}{{, 2015-12-31}}
}},
	att_donotupload={},
	att_private={false},
	att_projects={},
	att_tags={},
	att_techdoc={true},
	att_techdoc_key={TD:101707},
	att_url={http://web1-clone.research.att.com:81/techdocs_downloads/TD:101707_DS1_2016-01-06T05:48:06.386Z.pdf},
	author={Divesh Srivastava and Donatella Firmani and Barna Saha},
	institution={{Proceedings of the VLDB Endowment}},
	month={December},
	title={{Online Entity Resolution Using an Oracle}},
	year=2015,
}