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Normalization and outlier removal in class center-based firefly algorithm for missing value imputation

Overview of attention for article published in Journal of Big Data, October 2021
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Mentioned by

twitter
1 tweeter

Citations

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2 Dimensions

Readers on

mendeley
11 Mendeley
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Title
Normalization and outlier removal in class center-based firefly algorithm for missing value imputation
Published in
Journal of Big Data, October 2021
DOI 10.1186/s40537-021-00518-7
Authors

Heru Nugroho, Nugraha Priya Utama, Kridanto Surendro

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 %
Student > Doctoral Student 2 18%
Student > Master 2 18%
Student > Ph. D. Student 1 9%
Unspecified 1 9%
Professor > Associate Professor 1 9%
Other 1 9%
Unknown 3 27%
Readers by discipline Count As %
Computer Science 3 27%
Pharmacology, Toxicology and Pharmaceutical Science 1 9%
Unspecified 1 9%
Business, Management and Accounting 1 9%
Agricultural and Biological Sciences 1 9%
Other 0 0%
Unknown 4 36%

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 05 July 2022.
All research outputs
#17,927,024
of 22,165,427 outputs
Outputs from Journal of Big Data
#241
of 322 outputs
Outputs of similar age
#245,412
of 340,939 outputs
Outputs of similar age from Journal of Big Data
#1
of 1 outputs
Altmetric has tracked 22,165,427 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 322 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.6. 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 340,939 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them