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A novel approach to emotion recognition using local subset feature selection and modified Dempster-Shafer theory

Overview of attention for article published in Behavioral and Brain Functions, October 2018
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Mentioned by

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1 X user

Citations

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28 Dimensions

Readers on

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46 Mendeley
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Title
A novel approach to emotion recognition using local subset feature selection and modified Dempster-Shafer theory
Published in
Behavioral and Brain Functions, October 2018
DOI 10.1186/s12993-018-0149-4
Pubmed ID
Authors

Morteza Zangeneh Soroush, Keivan Maghooli, Seyed Kamaledin Setarehdan, Ali Motie Nasrabadi

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 11%
Researcher 4 9%
Lecturer 4 9%
Student > Doctoral Student 4 9%
Professor 3 7%
Other 10 22%
Unknown 16 35%
Readers by discipline Count As %
Computer Science 7 15%
Engineering 6 13%
Neuroscience 2 4%
Psychology 2 4%
Medicine and Dentistry 2 4%
Other 9 20%
Unknown 18 39%
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 01 November 2018.
All research outputs
#18,653,753
of 23,109,468 outputs
Outputs from Behavioral and Brain Functions
#288
of 392 outputs
Outputs of similar age
#268,917
of 350,967 outputs
Outputs of similar age from Behavioral and Brain Functions
#3
of 3 outputs
Altmetric has tracked 23,109,468 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 392 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.9. This one is in the 15th percentile – i.e., 15% 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 350,967 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.