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Hierarchical Clustering via Joint Between-Within Distances: Extending Ward's Minimum Variance Method

Overview of attention for article published in Journal of Classification, September 2005
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)

Mentioned by

blogs
1 blog
patent
1 patent
wikipedia
7 Wikipedia pages

Citations

dimensions_citation
515 Dimensions

Readers on

mendeley
196 Mendeley
citeulike
2 CiteULike
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Title
Hierarchical Clustering via Joint Between-Within Distances: Extending Ward's Minimum Variance Method
Published in
Journal of Classification, September 2005
DOI 10.1007/s00357-005-0012-9
Authors

Gabor J. Szekely, Maria L. Rizzo

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 196 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
France 1 <1%
Norway 1 <1%
Cuba 1 <1%
Ireland 1 <1%
United Kingdom 1 <1%
Australia 1 <1%
Unknown 188 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 45 23%
Student > Master 34 17%
Researcher 26 13%
Student > Doctoral Student 13 7%
Student > Bachelor 9 5%
Other 30 15%
Unknown 39 20%
Readers by discipline Count As %
Computer Science 27 14%
Engineering 19 10%
Agricultural and Biological Sciences 16 8%
Environmental Science 15 8%
Mathematics 12 6%
Other 57 29%
Unknown 50 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 18 November 2023.
All research outputs
#1,996,735
of 22,776,824 outputs
Outputs from Journal of Classification
#1
of 93 outputs
Outputs of similar age
#3,187
of 58,587 outputs
Outputs of similar age from Journal of Classification
#1
of 1 outputs
Altmetric has tracked 22,776,824 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 93 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done particularly well, scoring higher than 96% 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 58,587 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 94% of its contemporaries.
We're also able to compare this research output to 1 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