• Published 2013

Hierarchical Document Clustering Using Correlation Preserving Indexing

@inproceedings{Prabhakar2013HierarchicalDC,
  title={Hierarchical Document Clustering Using Correlation Preserving Indexing},
  author={Laishram Prabhakar},
  year={2013}
}
This paper presents a spectral clustering method called as correlation preserving indexing ( CPI). This method is performed in the correlation similar ity measure space. Correlation preserving indexing explicitly considers the manifold structure embedde d in the similarities between the documents. The ai m of CPI method is to find an optimal semantic subspace by maximizing the correlation between the documents i the local patches and simultaneously correlation in the patches outside are… CONTINUE READING

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References

Publications referenced by this paper.
SHOWING 1-10 OF 15 REFERENCES

Correlation Metric for Generalized Feature Extraction

  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2008
VIEW 1 EXCERPT

lation Pattern Recognition

R. D. Juday, B.V.K. Kumar, A. Mahalanobis, Corre
  • 2005
VIEW 1 EXCERPT

Recent Advances in C lustering: A Brief Review

S. Kotsiants, P. Pintelas
  • WSEAS Trans. Information Science and Applications, 2004.
  • 2004
VIEW 1 EXCERPT