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KDD
1995
ACM

Optimization and Simplification of Hierarchical Clusterings

13 years 10 months ago
Optimization and Simplification of Hierarchical Clusterings
Clustering is often used to discover structure in data. Clustering systems differ in the objective function used to evaluate clustering quality and the control strategy used to search the space of clusterings. In general, a search strategy cannot both (1) consistently construct clusterings of high quality and (2) be computationally inexpensive. However, we can partition the search so that a system inexpensively constructs ‘tentative’ clusterings for initial examination, followed by iterative optimization, which continues to search in background for improved clusterings. This paper evaluates hierarchical redistribution, which appears to be a novel optimization strategy in the clustering literature. A final component of search prunes tree-structured clusterings, thus simplifying them for analysis. In particular, resampling is used to significantly simplify hierarchical clusterings.
Douglas Fisher
Added 26 Aug 2010
Updated 26 Aug 2010
Type Conference
Year 1995
Where KDD
Authors Douglas Fisher
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