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» Clustering via Matrix Powering
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ICML
2010
IEEE
14 years 10 months ago
Power Iteration Clustering
We present a simple and scalable graph clustering method called power iteration clustering (PIC). PIC finds a very low-dimensional embedding of a dataset using truncated power ite...
Frank Lin, William W. Cohen
ECAI
2010
Springer
14 years 10 months ago
A Very Fast Method for Clustering Big Text Datasets
Large-scale text datasets have long eluded a family of particularly elegant and effective clustering methods that exploits the power of pair-wise similarities between data points ...
Frank Lin, William W. Cohen
80
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NIPS
2004
14 years 11 months ago
The Laplacian PDF Distance: A Cost Function for Clustering in a Kernel Feature Space
A new distance measure between probability density functions (pdfs) is introduced, which we refer to as the Laplacian pdf distance. The Laplacian pdf distance exhibits a remarkabl...
Robert Jenssen, Deniz Erdogmus, José Carlos...
WEBI
2005
Springer
15 years 3 months ago
Integrating Element and Term Semantics for Similarity-Based XML Document Clustering
Structured link vector model (SLVM) is a recently proposed document representation that takes into account both structural and semantic information for measuring XML document simi...
Jianwu Yang, William K. Cheung, Xiaoou Chen
SIGMOD
2011
ACM
269views Database» more  SIGMOD 2011»
14 years 12 days ago
Advancing data clustering via projective clustering ensembles
Projective Clustering Ensembles (PCE) are a very recent advance in data clustering research which combines the two powerful tools of clustering ensembles and projective clustering...
Francesco Gullo, Carlotta Domeniconi, Andrea Tagar...