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kProbLog: an algebraic Prolog for machine learning

Overview of attention for article published in Machine Learning, October 2017
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Mentioned by

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1 X user

Citations

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4 Dimensions

Readers on

mendeley
23 Mendeley
Title
kProbLog: an algebraic Prolog for machine learning
Published in
Machine Learning, October 2017
DOI 10.1007/s10994-017-5668-y
Authors

Francesco Orsini, Paolo Frasconi, Luc De Raedt

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

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 22%
Student > Doctoral Student 4 17%
Student > Master 4 17%
Researcher 3 13%
Professor 1 4%
Other 2 9%
Unknown 4 17%
Readers by discipline Count As %
Computer Science 13 57%
Agricultural and Biological Sciences 1 4%
Economics, Econometrics and Finance 1 4%
Physics and Astronomy 1 4%
Decision Sciences 1 4%
Other 0 0%
Unknown 6 26%
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 02 November 2017.
All research outputs
#18,575,277
of 23,007,053 outputs
Outputs from Machine Learning
#886
of 972 outputs
Outputs of similar age
#251,007
of 327,891 outputs
Outputs of similar age from Machine Learning
#5
of 5 outputs
Altmetric has tracked 23,007,053 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 972 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 2nd percentile – i.e., 2% 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 327,891 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one.