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| url = http://www.jea.acm.org/2000/EppsteinDynamic/
| volume = 5
| year = 2000| bibcode = 1999cs.......12014E }}.</ref><ref name="day-edels">{{citation
| last1 = Day | first1 = William H. E.
| last2 = Edelsbrunner | first2 = Herbert | author2-link = Herbert Edelsbrunner
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| series = Massive Computing
| title = Handbook of massive data sets
| journal = Handbook of massive data sets
| url = https://books.google.com/books?id=_VI0LITp3ecC&pg=PA513
| volume = 4
| year = 2002
}}.</ref>
*Initialize the set of active clusters to consist of {{mvar|n}} one-point clusters, one for each input point.
*Let {{mvar|S}} be a [[Stack (data structure)|stack data structure]], initially empty, the elements of which will be active clusters.
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| arxiv=1109.2378v1
| title=Modern hierarchical, agglomerative clustering algorithms
| volume=1109
| year=2011 }}.</ref> Following the earlier discussion of the value of defining cluster distances recursively (so that [[memoization]] can be used▼
| pages=arXiv:1109.2378
| year=2011 | bibcode=2011arXiv1109.2378M
▲
to greatly speed up distance computations), care must be taken with recursively defined distances so that they are not using the hierarchy in a way which is sensitive to merge order.
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