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Automatic Subspace Clustering of High Dimensional Data

Overview of attention for article published in Data Mining and Knowledge Discovery, July 2005
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Mentioned by

wikipedia
4 Wikipedia pages

Citations

dimensions_citation
244 Dimensions

Readers on

mendeley
165 Mendeley
citeulike
6 CiteULike
Title
Automatic Subspace Clustering of High Dimensional Data
Published in
Data Mining and Knowledge Discovery, July 2005
DOI 10.1007/s10618-005-1396-1
Authors

Rakesh Agrawal, Johannes Gehrke, Dimitrios Gunopulos, Prabhakar Raghavan

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 165 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 3%
Germany 3 2%
Japan 2 1%
Chile 1 <1%
France 1 <1%
Turkey 1 <1%
India 1 <1%
Switzerland 1 <1%
Brazil 1 <1%
Other 1 <1%
Unknown 148 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 50 30%
Student > Master 33 20%
Researcher 19 12%
Professor > Associate Professor 11 7%
Student > Doctoral Student 8 5%
Other 26 16%
Unknown 18 11%
Readers by discipline Count As %
Computer Science 85 52%
Engineering 11 7%
Agricultural and Biological Sciences 8 5%
Mathematics 6 4%
Environmental Science 5 3%
Other 22 13%
Unknown 28 17%
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 17 April 2019.
All research outputs
#7,917,073
of 23,854,458 outputs
Outputs from Data Mining and Knowledge Discovery
#156
of 546 outputs
Outputs of similar age
#20,891
of 57,923 outputs
Outputs of similar age from Data Mining and Knowledge Discovery
#2
of 2 outputs
Altmetric has tracked 23,854,458 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 546 research outputs from this source. They receive a mean Attention Score of 3.7. This one has gotten more attention than average, scoring higher than 56% 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 57,923 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.