↓ Skip to main content

ProbSky: Efficient Computation of Probabilistic Skyline Queries Over Distributed Data

Overview of attention for article published in IEEE Transactions on Knowledge and Data Engineering, February 2022
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age and source (74th percentile)

Mentioned by

twitter
2 X users

Readers on

mendeley
17 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Article details
Title
ProbSky: Efficient Computation of Probabilistic Skyline Queries Over Distributed Data
Published in
IEEE Transactions on Knowledge and Data Engineering, February 2022
DOI 10.1109/tkde.2022.3151740
Authors

Login to access the Attention Digest and the Sentiment Analysis related to this output.

Timeline Attention over time Attention Score history
Login to access the full charts related to this output.
Activity
Login to access the full charts related to this output.
X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Login to view Mendeley reader trends over time.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Lecturer 3 18%
Student > Bachelor 2 12%
Researcher 1 6%
Student > Master 1 6%
Unknown 10 59%
Readers by discipline
Readers by discipline Count As %
Computer Science 5 29%
Engineering 2 12%
Unknown 10 59%
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 26 February 2022.
All research outputs
#22,699,304
of 27,790,740 outputs
Outputs from IEEE Transactions on Knowledge and Data Engineering
#2,058
of 2,446 outputs
Outputs of similar age
#344,866
of 458,085 outputs
Outputs of similar age from IEEE Transactions on Knowledge and Data Engineering
#18
of 81 outputs
Altmetric has tracked 27,790,740 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 2,446 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 9th percentile – i.e., 9% 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 458,085 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 81 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.