Determining the Relative Accuracy of Attributes

Summary: Proposes a chase-based model with accuracy rules to determine when one tuple's A value is more accurate than another for the same entity. Analyzes termination, confluence, and a unique target te; offers a user-interactive framework and algorithms to compute te or top-k candidates, with experimental validation. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 4717
Venue: SIGMOD
Year: 2013
Pagerank: 4.5856065e-05
Overall Rank: 8,088 | 43.79%
DOI: -

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
3,054	Partial Results in Database Systems	2014	SIGMOD	7.6478475e-05
7,701	Counting and Enumerating (Preferred) Database Repairs	2017	PODS	4.6690279e-05

Outgoing Citations (Sorted by Pagerank)

Showing 8 of 8 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
8	Optimal Aggregation Algorithms for Middleware [Extended Abstract]	2001	PODS	0.0015436578
149	Trio: A System for Integrated Management of Data, Accuracy, and Lineage	2005	CIDR	0.00041085859
372	A Bayesian Approach to Discovering Truth from Conflicting Sources for Data Integration	2012	VLDB	0.00025371138
673	Supporting Top-k Join Queries in Relational Databases	2003	VLDB	0.00018325667
733	Discovering Data Quality Rules	2008	VLDB	0.00017428132
1,245	Truth Discovery and Copying Detection in a Dynamic World	2009	VLDB	0.00013080304
2,830	Interaction between Record Matching and Data Repairing	2011	SIGMOD	8.0515409e-05
2,965	Evaluating Rank Joins with Optimal Cost	2008	PODS	7.8049517e-05

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