↓ Skip to main content

Evaluation of high-level query languages based on MapReduce in Big Data

Overview of attention for article published in Journal of Big Data, October 2018
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
34 Mendeley
Title
Evaluation of high-level query languages based on MapReduce in Big Data
Published in
Journal of Big Data, October 2018
DOI 10.1186/s40537-018-0146-3
Authors

Marouane Birjali, Abderrahim Beni-Hssane, Mohammed Erritali

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

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 21%
Student > Master 6 18%
Student > Doctoral Student 2 6%
Student > Bachelor 2 6%
Professor 1 3%
Other 2 6%
Unknown 14 41%
Readers by discipline Count As %
Computer Science 10 29%
Engineering 3 9%
Agricultural and Biological Sciences 2 6%
Business, Management and Accounting 2 6%
Decision Sciences 1 3%
Other 1 3%
Unknown 15 44%
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 07 October 2018.
All research outputs
#15,547,315
of 23,106,390 outputs
Outputs from Journal of Big Data
#206
of 345 outputs
Outputs of similar age
#217,388
of 346,466 outputs
Outputs of similar age from Journal of Big Data
#11
of 15 outputs
Altmetric has tracked 23,106,390 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 345 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.2. This one is in the 25th percentile – i.e., 25% 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 346,466 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.