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Subjective interestingness of subgraph patterns

Overview of attention for article published in Machine Learning, January 2016
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

Mentioned by

twitter
2 X users

Citations

dimensions_citation
20 Dimensions

Readers on

mendeley
26 Mendeley
Title
Subjective interestingness of subgraph patterns
Published in
Machine Learning, January 2016
DOI 10.1007/s10994-015-5539-3
Authors

Matthijs van Leeuwen, Tijl De Bie, Eirini Spyropoulou, Cédric Mesnage

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 readers

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Professor 4 15%
Student > Master 4 15%
Student > Ph. D. Student 4 15%
Student > Doctoral Student 3 12%
Researcher 3 12%
Other 6 23%
Unknown 2 8%
Readers by discipline Count As %
Computer Science 20 77%
Business, Management and Accounting 2 8%
Earth and Planetary Sciences 1 4%
Engineering 1 4%
Unknown 2 8%
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 28 June 2016.
All research outputs
#13,458,480
of 22,849,304 outputs
Outputs from Machine Learning
#514
of 965 outputs
Outputs of similar age
#189,402
of 393,757 outputs
Outputs of similar age from Machine Learning
#4
of 10 outputs
Altmetric has tracked 22,849,304 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 965 research outputs from this source. They receive a mean Attention Score of 4.4. This one is in the 44th percentile – i.e., 44% 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 393,757 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 50% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.