Ward’s Hierarchical Agglomerative Clustering Method : Which Algorithms Implement Ward’s Criterion?
- Submitting institution
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The University of Huddersfield
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 67
- Type
- D - Journal article
- DOI
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10.1007/s00357-014-9161-z
- Title of journal
- Journal of Classification
- Article number
- -
- First page
- 274
- Volume
- 31
- Issue
- 3
- ISSN
- 0176-4268
- Open access status
- Out of scope for open access requirements
- Month of publication
- October
- Year of publication
- 2014
- URL
-
-
- Supplementary information
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- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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1
- Research group(s)
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-
- Citation count
- 955
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Published in a Scimago Q1 journal, this paper's research has had a remarkable influence on the field of agglomerative hierarchical clustering (e.g. with over 100 cites per year and thousands of downloads https://link.springer.com/article/10.1007/s00357-014-9161-z, https://www.researchgate.net/publication/277665024_Ward%27s_Hierarchical_Agglomerative_Clustering_Method_Which_Algorithms_Implement_Ward%27s_Criterion). Notably, the programming language R contains a free software environment for statistical computing and graphics with more than two million users: the paper's research has led to an update to the hclust function in R (update "ward.D2", as evidenced in the descriptive details: https://www.rdocumentation.org/packages/stats/versions/3.6.2/topics/hclust).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -