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A Tutorial on Support Vector Machines for Pattern Recognition

Overview of attention for article published in Data Mining and Knowledge Discovery, June 1998
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#9 of 637)
  • High Attention Score compared to outputs of the same age (98th percentile)

Mentioned by

news
1 news outlet
twitter
3 X users
patent
25 patents
facebook
1 Facebook page
wikipedia
1 Wikipedia page

Citations

dimensions_citation
12118 Dimensions

Readers on

mendeley
26300 Mendeley
citeulike
46 CiteULike
connotea
4 Connotea
Title
A Tutorial on Support Vector Machines for Pattern Recognition
Published in
Data Mining and Knowledge Discovery, June 1998
DOI 10.1023/a:1009715923555
Authors

Christopher J.C. Burges

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 26,300 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 333 1%
United Kingdom 120 <1%
Germany 118 <1%
Brazil 102 <1%
India 91 <1%
Spain 64 <1%
China 64 <1%
France 57 <1%
Indonesia 41 <1%
Other 676 3%
Unknown 24634 94%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6287 24%
Student > Bachelor 5082 19%
Student > Ph. D. Student 4731 18%
Researcher 2645 10%
Student > Postgraduate 2006 8%
Other 4559 17%
Unknown 990 4%
Readers by discipline Count As %
Computer Science 15312 58%
Engineering 7091 27%
Environmental Science 428 2%
Agricultural and Biological Sciences 390 1%
Mathematics 213 <1%
Other 1452 6%
Unknown 1414 5%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 24. 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 06 June 2022.
All research outputs
#1,580,619
of 25,374,917 outputs
Outputs from Data Mining and Knowledge Discovery
#9
of 637 outputs
Outputs of similar age
#632
of 33,275 outputs
Outputs of similar age from Data Mining and Knowledge Discovery
#1
of 2 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 637 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done particularly well, scoring higher than 98% 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 33,275 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 98% of its contemporaries.
We're also able to compare this research output to 2 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