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KDD
2005
ACM
118views Data Mining» more  KDD 2005»
15 years 10 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»
14 years 9 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»
15 years 1 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
14 years 11 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
14 years 9 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