CCE: A Coupled Framework of Clustering Ensembles

AAAI 2012 pp. 2455-2456

doi:10.1609/AAAI.V26I1.8411 /aaai/2012/she2012aaai-cce/

Abstract

Clustering ensemble mainly relies on the pairwise similarity to capture the consensus function. However, it usually considers each base clustering independently, and treats the similarity measure roughly with either 0 or 1. To address these two issues, we propose a coupled framework of clustering ensembles CCE, and exemplify it with the coupled version CCSPA for CSPA. Experiments demonstrate the superiority of CCSPA over baseline approaches in terms of the clustering accuracy.

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Text

She et al. "CCE: A Coupled Framework of Clustering Ensembles." AAAI Conference on Artificial Intelligence, 2012. doi:10.1609/AAAI.V26I1.8411

Markdown

[She et al. "CCE: A Coupled Framework of Clustering Ensembles." AAAI Conference on Artificial Intelligence, 2012.](https://mlanthology.org/aaai/2012/she2012aaai-cce/) doi:10.1609/AAAI.V26I1.8411

BibTeX

@inproceedings{she2012aaai-cce,
  title     = {{CCE: A Coupled Framework of Clustering Ensembles}},
  author    = {She, Zhong and Wang, Can and Cao, Longbing},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2012},
  pages     = {2455-2456},
  doi       = {10.1609/AAAI.V26I1.8411},
  url       = {https://mlanthology.org/aaai/2012/she2012aaai-cce/}
}