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Copyright policy ) Thomas H. Herzog; Fritz Scheuren; William E. Winkler;
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AbstractThis article describes methods for matching duplicates within or across files using non‐unique identifiers such as first name, last name, date of birth, address, and other characteristics. Copyright © 2010 John Wiley & Sons, Inc.This article is categorized under:Statistical and Graphical Methods of Data Analysis > Data Reduction, Smoothing, and Filtering
- University of Chicago United States
- National Opinion Research Center United States
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).29 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
selected citations
Citations provided by BIP!
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
Citations provided by BIP!popularityPopularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
Popularity provided by BIP! 29
Top 10%
Top 10%
Average
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