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Parallel Patterns for Window-Based Stateful Operators on Data Streams: An Algorithmic Skeleton Approach

Overview of attention for article published in International Journal of Parallel Programming, March 2016
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About this Attention Score

  • Among the highest-scoring outputs from this source (#29 of 170)
  • Above-average Attention Score compared to outputs of the same age (55th percentile)

Mentioned by

wikipedia
3 Wikipedia pages

Readers on

mendeley
37 Mendeley
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Title
Parallel Patterns for Window-Based Stateful Operators on Data Streams: An Algorithmic Skeleton Approach
Published in
International Journal of Parallel Programming, March 2016
DOI 10.1007/s10766-016-0413-x
Authors

Tiziano De Matteis, Gabriele Mencagli

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 3%
Unknown 36 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 24%
Student > Master 7 19%
Researcher 4 11%
Student > Doctoral Student 3 8%
Lecturer 2 5%
Other 6 16%
Unknown 6 16%
Readers by discipline Count As %
Computer Science 28 76%
Engineering 2 5%
Unknown 7 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 24 January 2017.
All research outputs
#7,490,851
of 22,896,955 outputs
Outputs from International Journal of Parallel Programming
#29
of 170 outputs
Outputs of similar age
#107,632
of 300,449 outputs
Outputs of similar age from International Journal of Parallel Programming
#1
of 4 outputs
Altmetric has tracked 22,896,955 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 170 research outputs from this source. They receive a mean Attention Score of 3.2. This one is in the 24th percentile – i.e., 24% 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 300,449 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.
We're also able to compare this research output to 4 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