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Intelligent cloud workflow management and scheduling method for big data applications

Overview of attention for article published in Journal of Cloud Computing, July 2020
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Mentioned by

twitter
1 X user

Citations

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19 Dimensions

Readers on

mendeley
24 Mendeley
Title
Intelligent cloud workflow management and scheduling method for big data applications
Published in
Journal of Cloud Computing, July 2020
DOI 10.1186/s13677-020-00177-8
Authors

Yannian Hu, Hui Wang, Wenge Ma

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

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 13%
Student > Bachelor 2 8%
Student > Master 2 8%
Professor 2 8%
Lecturer 1 4%
Other 3 13%
Unknown 11 46%
Readers by discipline Count As %
Computer Science 6 25%
Engineering 3 13%
Biochemistry, Genetics and Molecular Biology 1 4%
Medicine and Dentistry 1 4%
Energy 1 4%
Other 0 0%
Unknown 12 50%
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 22 July 2020.
All research outputs
#18,734,471
of 23,221,875 outputs
Outputs from Journal of Cloud Computing
#152
of 256 outputs
Outputs of similar age
#301,611
of 399,627 outputs
Outputs of similar age from Journal of Cloud Computing
#6
of 18 outputs
Altmetric has tracked 23,221,875 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 256 research outputs from this source. They receive a mean Attention Score of 2.1. This one is in the 1st percentile – i.e., 1% 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 399,627 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 18 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.