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Online Feature Selection (OFS) with Accelerated Bat Algorithm (ABA) and Ensemble Incremental Deep Multiple Layer Perceptron (EIDMLP) for big data streams

Overview of attention for article published in Journal of Big Data, November 2019
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Mentioned by

twitter
1 X user

Citations

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15 Dimensions

Readers on

mendeley
27 Mendeley
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Title
Online Feature Selection (OFS) with Accelerated Bat Algorithm (ABA) and Ensemble Incremental Deep Multiple Layer Perceptron (EIDMLP) for big data streams
Published in
Journal of Big Data, November 2019
DOI 10.1186/s40537-019-0267-3
Authors

D. Renuka Devi, S. Sasikala

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

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 4 15%
Student > Ph. D. Student 3 11%
Student > Doctoral Student 3 11%
Lecturer > Senior Lecturer 2 7%
Professor 2 7%
Other 7 26%
Unknown 6 22%
Readers by discipline Count As %
Computer Science 13 48%
Business, Management and Accounting 2 7%
Engineering 2 7%
Agricultural and Biological Sciences 1 4%
Social Sciences 1 4%
Other 1 4%
Unknown 7 26%
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 21 November 2019.
All research outputs
#18,699,437
of 23,177,498 outputs
Outputs from Journal of Big Data
#264
of 346 outputs
Outputs of similar age
#335,977
of 457,712 outputs
Outputs of similar age from Journal of Big Data
#11
of 16 outputs
Altmetric has tracked 23,177,498 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 346 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.3. This one is in the 5th percentile – i.e., 5% 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 457,712 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.