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SIGMOD
2007
ACM

Benchmarking declarative approximate selection predicates

14 years 11 months ago
Benchmarking declarative approximate selection predicates
Declarative data quality has been an active research topic. The fundamental principle behind a declarative approach to data quality is the use of declarative statements to realize data quality primitives on top of any relational data source. A primary advantage of such an approach is the ease of use and integration with existing applications. Over the last few years several similarity predicates have been proposed for common quality primitives (approximate selections, joins, etc) and have been fully expressed using declarative SQL statements. In this paper we propose new similarity predicates along with their declarative realization, based on notions of probabilistic information retrieval. In particular we show how language models and hidden Markov models can be utilized as similarity predicates for data quality and present their full declarative instantiation. We also show how other scoring methods from information retrieval, can be utilized in a similar setting. We then present full...
Amit Chandel, Oktie Hassanzadeh, Nick Koudas, Moha
Added 08 Dec 2009
Updated 08 Dec 2009
Type Conference
Year 2007
Where SIGMOD
Authors Amit Chandel, Oktie Hassanzadeh, Nick Koudas, Mohammad Sadoghi, Divesh Srivastava
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