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ICDE
2007
IEEE
211views Database» more  ICDE 2007»
13 years 11 months ago
Document Representation and Dimension Reduction for Text Clustering
Increasingly large text datasets and the high dimensionality associated with natural language create a great challenge in text mining. In this research, a systematic study is cond...
M. Mahdi Shafiei, Singer Wang, Roger Zhang, Evange...
AI
2005
Springer
13 years 10 months ago
Comparing Dimension Reduction Techniques for Document Clustering
In this research, a systematic study is conducted of four dimension reduction techniques for the text clustering problem, using five benchmark data sets. Of the four methods -- Ind...
Bin Tang, Michael A. Shepherd, Malcolm I. Heywood,...
SDM
2007
SIAM
177views Data Mining» more  SDM 2007»
13 years 6 months ago
Bursty Feature Representation for Clustering Text Streams
Text representation plays a crucial role in classical text mining, where the primary focus was on static text. Nevertheless, well-studied static text representations including TFI...
Qi He, Kuiyu Chang, Ee-Peng Lim, Jun Zhang
ESANN
2007
13 years 6 months ago
Kernel PCA based clustering for inducing features in text categorization
We study dimensionality reduction or feature selection in text document categorization problem. We focus on the first step in building text categorization systems, that is the cho...
Zsolt Minier, Lehel Csató
ICDE
2012
IEEE
227views Database» more  ICDE 2012»
11 years 7 months ago
Horizontal Reduction: Instance-Level Dimensionality Reduction for Similarity Search in Large Document Databases
—Dimensionality reduction is essential in text mining since the dimensionality of text documents could easily reach several tens of thousands. Most recent efforts on dimensionali...
Min-Soo Kim 0001, Kyu-Young Whang, Yang-Sae Moon