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Information maximization clustering via multi-view self-labelling

Overview of attention for article published in Knowledge-Based Systems, August 2022
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  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

twitter
3 X users

Readers on

mendeley
36 Mendeley
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Article details
Title
Information maximization clustering via multi-view self-labelling
Published in
Knowledge-Based Systems, August 2022
DOI 10.1016/j.knosys.2022.109042
Authors

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Timeline Attention over time Attention Score history
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Activity
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X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 5 14%
Student > Bachelor 3 8%
Student > Ph. D. Student 3 8%
Researcher 3 8%
Lecturer > Senior Lecturer 1 3%
Other 1 3%
Unknown 20 56%
Readers by discipline
Readers by discipline Count As %
Computer Science 11 31%
Engineering 4 11%
Social Sciences 1 3%
Unknown 20 56%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 20 October 2021.
All research outputs
#17,852,344
of 27,790,740 outputs
Outputs from Knowledge-Based Systems
#679
of 1,986 outputs
Outputs of similar age
#224,478
of 440,542 outputs
Outputs of similar age from Knowledge-Based Systems
#11
of 234 outputs
Altmetric has tracked 27,790,740 research outputs across all sources so far. This one is in the 33rd percentile – i.e., 33% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,986 research outputs from this source. They receive a mean Attention Score of 2.5. This one has gotten more attention than average, scoring higher than 64% of its peers.
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 440,542 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 234 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.