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
Citations
Publications citing this paper.
DOCUMENT CLUSTERING USING CO-WORD ANALYSIS AND FORMATION OF KEYWORD AGAINST DOCUMENT MATRIX
VIEW 1 EXCERPT
CITES METHODS
References
Publications referenced by this paper.
SHOWING 1-10 OF 15 REFERENCES
Indexing by Latent Semantic Analysis
VIEW 6 EXCERPTS
HIGHLY INFLUENTIAL
Correlation Metric for Generalized Feature Extraction
VIEW 1 EXCERPT
lation Pattern Recognition
VIEW 1 EXCERPT
Recent Advances in C lustering: A Brief Review
VIEW 1 EXCERPT