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Collective Mining of Bayesian Networks from Distributed Heterogeneous Data

Overview of attention for article published in Knowledge and Information Systems, March 2004
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Mentioned by

patent
2 patents

Readers on

mendeley
43 Mendeley
citeulike
1 CiteULike
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Title
Collective Mining of Bayesian Networks from Distributed Heterogeneous Data
Published in
Knowledge and Information Systems, March 2004
DOI 10.1007/s10115-003-0107-8
Authors

R. Chen, K. Sivakumar, H. Kargupta

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 5%
France 1 2%
Virgin Islands, U.S. 1 2%
Unknown 39 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 19%
Student > Master 7 16%
Researcher 7 16%
Student > Doctoral Student 5 12%
Professor > Associate Professor 5 12%
Other 8 19%
Unknown 3 7%
Readers by discipline Count As %
Computer Science 25 58%
Engineering 4 9%
Social Sciences 3 7%
Agricultural and Biological Sciences 2 5%
Environmental Science 2 5%
Other 5 12%
Unknown 2 5%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 05 January 2016.
All research outputs
#7,866,480
of 23,849,058 outputs
Outputs from Knowledge and Information Systems
#76
of 614 outputs
Outputs of similar age
#19,603
of 55,770 outputs
Outputs of similar age from Knowledge and Information Systems
#1
of 3 outputs
Altmetric has tracked 23,849,058 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 614 research outputs from this source. They receive a mean Attention Score of 2.3. This one has gotten more attention than average, scoring higher than 65% 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 55,770 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 3 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them