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Learning the Semantics of Notational Systems with a Semiotic Cognitive Automaton

Overview of attention for article published in Cognitive Computation, March 2016
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

twitter
3 X users

Readers on

mendeley
12 Mendeley
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Title
Learning the Semantics of Notational Systems with a Semiotic Cognitive Automaton
Published in
Cognitive Computation, March 2016
DOI 10.1007/s12559-015-9378-0
Authors

Valerio Targon

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 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Russia 1 8%
Unknown 11 92%

Demographic breakdown

Readers by professional status Count As %
Lecturer 2 17%
Student > Postgraduate 2 17%
Student > Bachelor 2 17%
Lecturer > Senior Lecturer 1 8%
Researcher 1 8%
Other 1 8%
Unknown 3 25%
Readers by discipline Count As %
Mathematics 3 25%
Linguistics 2 17%
Computer Science 2 17%
Psychology 1 8%
Unknown 4 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 03 August 2016.
All research outputs
#17,008,464
of 24,998,746 outputs
Outputs from Cognitive Computation
#165
of 436 outputs
Outputs of similar age
#187,033
of 306,292 outputs
Outputs of similar age from Cognitive Computation
#6
of 26 outputs
Altmetric has tracked 24,998,746 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 436 research outputs from this source. They receive a mean Attention Score of 2.6. This one has gotten more attention than average, scoring higher than 52% 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 306,292 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.