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Swoosh: a generic approach to entity resolution

Overview of attention for article published in The VLDB Journal — The International Journal on Very Large Data Bases, March 2008
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About this Attention Score

  • Among the highest-scoring outputs from this source (#21 of 113)
  • Good Attention Score compared to outputs of the same age (66th percentile)

Mentioned by

patent
1 patent

Citations

dimensions_citation
216 Dimensions

Readers on

mendeley
215 Mendeley
citeulike
9 CiteULike
Title
Swoosh: a generic approach to entity resolution
Published in
The VLDB Journal — The International Journal on Very Large Data Bases, March 2008
DOI 10.1007/s00778-008-0098-x
Authors

Omar Benjelloun, Hector Garcia-Molina, David Menestrina, Qi Su, Steven Euijong Whang, Jennifer Widom

Mendeley readers

The data shown below were compiled from readership statistics for 215 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 10 5%
United Kingdom 6 3%
Brazil 5 2%
France 3 1%
Australia 3 1%
Ireland 3 1%
China 2 <1%
Portugal 2 <1%
Turkey 1 <1%
Other 9 4%
Unknown 171 80%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 73 34%
Researcher 44 20%
Other 23 11%
Student > Master 22 10%
Student > Bachelor 11 5%
Other 42 20%
Readers by discipline Count As %
Computer Science 159 74%
Arts and Humanities 12 6%
Social Sciences 11 5%
Unspecified 11 5%
Engineering 4 2%
Other 18 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 23 July 2015.
All research outputs
#2,721,849
of 10,083,283 outputs
Outputs from The VLDB Journal — The International Journal on Very Large Data Bases
#21
of 113 outputs
Outputs of similar age
#37,294
of 113,887 outputs
Outputs of similar age from The VLDB Journal — The International Journal on Very Large Data Bases
#1
of 1 outputs
Altmetric has tracked 10,083,283 research outputs across all sources so far. This one has received more attention than most of these and is in the 55th percentile.
So far Altmetric has tracked 113 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 18th percentile – i.e., 18% of its peers scored the same or lower than it.
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 113,887 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% 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