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ICTAI
2008
IEEE
14 years 3 months ago
Knee Point Detection on Bayesian Information Criterion
The main challenge of cluster analysis is that the number of clusters or the number of model parameters is seldom known, and it must therefore be determined before clustering. Bay...
Qinpei Zhao, Mantao Xu, Pasi Fränti
ICML
2005
IEEE
14 years 9 months ago
Multi-way distributional clustering via pairwise interactions
We present a novel unsupervised learning scheme that simultaneously clusters variables of several types (e.g., documents, words and authors) based on pairwise interactions between...
Ron Bekkerman, Ran El-Yaniv, Andrew McCallum
ICDM
2009
IEEE
176views Data Mining» more  ICDM 2009»
13 years 6 months ago
SISC: A Text Classification Approach Using Semi Supervised Subspace Clustering
Text classification poses some specific challenges. One such challenge is its high dimensionality where each document (data point) contains only a small subset of them. In this pap...
Mohammad Salim Ahmed, Latifur Khan
ICDAR
2011
IEEE
12 years 8 months ago
Word Retrieval in Historical Document Using Character-Primitives
Word searching and indexing in historical document collections is a challenging problem because, characters in these documents are often touching or broken due to degradation/agei...
Partha Pratim Roy, Jean-Yves Ramel, Nicolas Ragot
SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
13 years 10 months ago
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Levent Ertöz, Michael Steinbach, Vipin Kumar