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Simple Iterative Heuristics for Correlation Clustering

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Author

Summary, in English

A straightforward natural iterative heuristic for correlation clustering in the general setting is to start from singleton clusters and whenever merging two clusters improves the current quality score merge them into a single cluster. We analyze the approximation and complexity aspects of this heuristic and its randomized variant where two clusters to merge are chosen uniformly at random among cluster pairs amenable to merge.

Publishing year

2014

Language

English

Pages

264-271

Publication/Series

Large-Scale Scientific Computing, LSSC 2013

Volume

8353

Document type

Conference paper

Publisher

Springer

Topic

  • Computer Science

Conference name

9th International Conference on Large-Scale Scientific Computations (LSSC)

Conference date

2013-06-03 - 2013-06-07

Status

Published

ISBN/ISSN/Other

  • ISSN: 1611-3349
  • ISSN: 0302-9743