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» A Semi-Supervised Document Clustering Algorithm Based on EM
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SDM
2008
SIAM
168views Data Mining» more  SDM 2008»
13 years 6 months ago
Semi-Supervised Clustering via Matrix Factorization
The recent years have witnessed a surge of interests of semi-supervised clustering methods, which aim to cluster the data set under the guidance of some supervisory information. U...
Fei Wang, Tao Li, Changshui Zhang
TKDE
2012
245views Formal Methods» more  TKDE 2012»
11 years 7 months ago
Semi-Supervised Maximum Margin Clustering with Pairwise Constraints
—The pairwise constraints specifying whether a pair of samples should be grouped together or not have been successfully incorporated into the conventional clustering methods such...
Hong Zeng, Yiu-ming Cheung
ICPR
2010
IEEE
13 years 7 months ago
A Semi-Supervised Gaussian Mixture Model for Image Segmentation
In this paper, the results of a semi-supervised approach based on the Expectation-Maximisation algorithm for model-based clustering are presented. We show in this work that, if th...
Adolfo Martínez-Usó, F. Pla, Jose Martínez Soto...
KDD
2002
ACM
147views Data Mining» more  KDD 2002»
14 years 5 months ago
A parallel learning algorithm for text classification
Text classification is the process of classifying documents into predefined categories based on their content. Existing supervised learning algorithms to automatically classify te...
Canasai Kruengkrai, Chuleerat Jaruskulchai
ICMCS
2006
IEEE
142views Multimedia» more  ICMCS 2006»
13 years 11 months ago
FEMA: A Fast Expectation Maximization Algorithm based on Grid and PCA
EM algorithm is an important unsupervised clustering algorithm, but the algorithm has several limitations. In this paper, we propose a fast EM algorithm (FEMA) to address the limi...
Zhiwen Yu, Hau-San Wong