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The max-min hill-climbing Bayesian network structure learning algorithm

Overview of attention for article published in Machine Learning, March 2006
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#37 of 1,259)
  • High Attention Score compared to outputs of the same age (95th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

news
1 news outlet
twitter
2 X users
patent
15 patents

Citations

dimensions_citation
1220 Dimensions

Readers on

mendeley
683 Mendeley
citeulike
6 CiteULike
Title
The max-min hill-climbing Bayesian network structure learning algorithm
Published in
Machine Learning, March 2006
DOI 10.1007/s10994-006-6889-7
Authors

Ioannis Tsamardinos, Laura E. Brown, Constantin F. Aliferis

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

Geographical breakdown

Country Count As %
United States 7 1%
United Kingdom 5 <1%
China 4 <1%
France 3 <1%
India 2 <1%
Turkey 1 <1%
Virgin Islands, U.S. 1 <1%
Switzerland 1 <1%
Australia 1 <1%
Other 12 2%
Unknown 646 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 190 28%
Student > Master 101 15%
Researcher 83 12%
Student > Doctoral Student 41 6%
Student > Bachelor 37 5%
Other 109 16%
Unknown 122 18%
Readers by discipline Count As %
Computer Science 233 34%
Engineering 86 13%
Agricultural and Biological Sciences 48 7%
Mathematics 38 6%
Medicine and Dentistry 19 3%
Other 108 16%
Unknown 151 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 20. 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 12 March 2024.
All research outputs
#1,890,409
of 25,837,817 outputs
Outputs from Machine Learning
#37
of 1,259 outputs
Outputs of similar age
#3,582
of 86,938 outputs
Outputs of similar age from Machine Learning
#2
of 9 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,259 research outputs from this source. They receive a mean Attention Score of 4.2. This one has done particularly well, scoring higher than 97% 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 86,938 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 7 of them.