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A survey of feature selection methods for Gaussian mixture models and hidden Markov models

Overview of attention for article published in Artificial Intelligence Review, September 2017
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Mentioned by

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1 X user
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1 Facebook page

Citations

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39 Dimensions

Readers on

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63 Mendeley
Title
A survey of feature selection methods for Gaussian mixture models and hidden Markov models
Published in
Artificial Intelligence Review, September 2017
DOI 10.1007/s10462-017-9581-3
Authors

Stephen Adams, Peter A. Beling

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

Geographical breakdown

Country Count As %
Unknown 63 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 17 27%
Student > Ph. D. Student 15 24%
Professor 5 8%
Student > Doctoral Student 3 5%
Student > Bachelor 3 5%
Other 7 11%
Unknown 13 21%
Readers by discipline Count As %
Engineering 19 30%
Computer Science 17 27%
Mathematics 3 5%
Social Sciences 2 3%
Biochemistry, Genetics and Molecular Biology 1 2%
Other 3 5%
Unknown 18 29%
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 02 October 2017.
All research outputs
#17,916,739
of 23,005,189 outputs
Outputs from Artificial Intelligence Review
#536
of 703 outputs
Outputs of similar age
#229,540
of 320,358 outputs
Outputs of similar age from Artificial Intelligence Review
#5
of 6 outputs
Altmetric has tracked 23,005,189 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 703 research outputs from this source. They receive a mean Attention Score of 3.9. This one is in the 12th percentile – i.e., 12% 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 320,358 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one.