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Privacy-preserving record linkage using Bloom filters

Overview of attention for article published in BMC Medical Informatics and Decision Making, August 2009
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)

Mentioned by

twitter
9 tweeters
patent
1 patent
wikipedia
1 Wikipedia page

Citations

dimensions_citation
227 Dimensions

Readers on

mendeley
134 Mendeley
citeulike
7 CiteULike
connotea
1 Connotea
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Title
Privacy-preserving record linkage using Bloom filters
Published in
BMC Medical Informatics and Decision Making, August 2009
DOI 10.1186/1472-6947-9-41
Pubmed ID
Authors

Rainer Schnell, Tobias Bachteler, Jörg Reiher

Abstract

Combining multiple databases with disjunctive or additional information on the same person is occurring increasingly throughout research. If unique identification numbers for these individuals are not available, probabilistic record linkage is used for the identification of matching record pairs. In many applications, identifiers have to be encrypted due to privacy concerns.

Twitter Demographics

The data shown below were collected from the profiles of 9 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 134 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 2%
Malaysia 2 1%
Brazil 2 1%
Switzerland 1 <1%
Australia 1 <1%
Sweden 1 <1%
Canada 1 <1%
Slovenia 1 <1%
Japan 1 <1%
Other 0 0%
Unknown 121 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 35 26%
Student > Ph. D. Student 28 21%
Student > Master 13 10%
Student > Bachelor 10 7%
Professor > Associate Professor 9 7%
Other 31 23%
Unknown 8 6%
Readers by discipline Count As %
Computer Science 60 45%
Medicine and Dentistry 19 14%
Social Sciences 7 5%
Mathematics 6 4%
Nursing and Health Professions 5 4%
Other 20 15%
Unknown 17 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 13. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 May 2022.
All research outputs
#2,376,390
of 22,381,487 outputs
Outputs from BMC Medical Informatics and Decision Making
#168
of 1,961 outputs
Outputs of similar age
#7,294
of 77,775 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#1
of 1 outputs
Altmetric has tracked 22,381,487 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,961 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done particularly well, scoring higher than 91% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 77,775 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them