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Mining significant association rules from uncertain data

Overview of attention for article published in Data Mining and Knowledge Discovery, January 2016
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
1 X user

Citations

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14 Dimensions

Readers on

mendeley
32 Mendeley
Title
Mining significant association rules from uncertain data
Published in
Data Mining and Knowledge Discovery, January 2016
DOI 10.1007/s10618-015-0446-6
Authors

Anshu Zhang, Wenzhong Shi, Geoffrey I. Webb

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

Geographical breakdown

Country Count As %
Russia 1 3%
Korea, Republic of 1 3%
Unknown 30 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 38%
Student > Master 6 19%
Researcher 5 16%
Student > Doctoral Student 2 6%
Lecturer 2 6%
Other 1 3%
Unknown 4 13%
Readers by discipline Count As %
Computer Science 15 47%
Engineering 4 13%
Business, Management and Accounting 3 9%
Biochemistry, Genetics and Molecular Biology 1 3%
Earth and Planetary Sciences 1 3%
Other 1 3%
Unknown 7 22%
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 22 January 2016.
All research outputs
#16,172,769
of 23,854,458 outputs
Outputs from Data Mining and Knowledge Discovery
#354
of 546 outputs
Outputs of similar age
#238,519
of 401,537 outputs
Outputs of similar age from Data Mining and Knowledge Discovery
#4
of 5 outputs
Altmetric has tracked 23,854,458 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 546 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 22nd percentile – i.e., 22% 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 401,537 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% 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.