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Constrained self-organizing feature map to preserve feature extraction topology

Overview of attention for article published in Neural Computing & Applications, May 2016
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

Mentioned by

twitter
2 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
11 Mendeley
Title
Constrained self-organizing feature map to preserve feature extraction topology
Published in
Neural Computing & Applications, May 2016
DOI 10.1007/s00521-016-2346-0
Authors

Jorge Azorin-Lopez, Marcelo Saval-Calvo, Andres Fuster-Guillo, Jose Garcia-Rodriguez, Higinio Mora-Mora

Twitter Demographics

The data shown below were collected from the profiles of 2 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 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 5 45%
Student > Postgraduate 2 18%
Student > Doctoral Student 2 18%
Researcher 1 9%
Student > Bachelor 1 9%
Other 0 0%
Readers by discipline Count As %
Computer Science 8 73%
Engineering 2 18%
Unspecified 1 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 10 June 2016.
All research outputs
#7,263,218
of 12,225,503 outputs
Outputs from Neural Computing & Applications
#84
of 185 outputs
Outputs of similar age
#136,864
of 276,361 outputs
Outputs of similar age from Neural Computing & Applications
#4
of 13 outputs
Altmetric has tracked 12,225,503 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 185 research outputs from this source. They receive a mean Attention Score of 2.2. This one has gotten more attention than average, scoring higher than 55% 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 276,361 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.