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Author Vogel, Tobias ♦ Heise, Arvid ♦ Draisbach, Uwe ♦ Lange, Dustin ♦ Naumann, Felix
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2014
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Annealing standard ♦ Classification ♦ Duplicate detection ♦ Gold standard ♦ Silver standard
Abstract Duplicates in a database are one of the prime causes of poor data quality and are at the same time among the most difficult data quality problems to alleviate. To detect and remove such duplicates, many commercial and academic products and methods have been developed. The evaluation of such systems is usually in need of pre-classified results. Such gold standards are often expensive to come by (much manual classification is necessary), not representative (too small or too synthetic), and proprietary and thus preclude repetition (company-internal data). This lament has been uttered in many papers and even more paper reviews. The proposed annealing standard is a structured set of duplicate detection results, some of which are manually verified and some of which are merely validated by many classifiers. As more and more classifiers are evaluated against the annealing standard, more and more results are verified and validation becomes more and more confident. We formally define gold, silver, and the annealing standard and their maintenance. Experiments show how quickly an annealing standard converges to a gold standard. Finally, we provide an annealing standard for 750,000 CDs to the duplicate detection community.
ISSN 19361955
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2014-09-04
Publisher Place New York
e-ISSN 19361963
Journal Journal of Data and Information Quality (JDIQ)
Volume Number 5
Issue Number 1-2
Page Count 25
Starting Page 1
Ending Page 25


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Source: ACM Digital Library