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KDD
2005
ACM
118views Data Mining» more  KDD 2005»
14 years 5 months ago
On the use of linear programming for unsupervised text classification
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
Mark Sandler
TIP
2002
179views more  TIP 2002»
13 years 4 months ago
Unsupervised image classification, segmentation, and enhancement using ICA mixture models
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...
Te-Won Lee, Michael S. Lewicki
DEXA
2006
Springer
143views Database» more  DEXA 2006»
13 years 8 months ago
Multivariate Stream Data Classification Using Simple Text Classifiers
We introduce a classification framework for continuous multivariate stream data. The proposed approach works in two steps. In the preprocessing step, it takes as input a sliding wi...
Sungbo Seo, Jaewoo Kang, Dongwon Lee, Keun Ho Ryu
RIAO
2004
13 years 5 months ago
Unsupervised Learning with Term Clustering for Thematic Segmentation of Texts
In this paper we introduce a machine learning approach for automatic text segmentation. Our text segmenter clusters text-segments containing similar concepts. It first discovers th...
Marc Caillet, Jean-François Pessiot, Massih...
SIGIR
2002
ACM
13 years 4 months ago
Unsupervised document classification using sequential information maximization
We present a novel sequential clustering algorithm which is motivated by the Information Bottleneck (IB) method. In contrast to the agglomerative IB algorithm, the new sequential ...
Noam Slonim, Nir Friedman, Naftali Tishby