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AI
2005
Springer
14 years 1 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,...
CIKM
2010
Springer
13 years 6 months ago
Decomposing background topics from keywords by principal component pursuit
Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools s...
Kerui Min, Zhengdong Zhang, John Wright, Yi Ma
SAC
2006
ACM
13 years 7 months ago
High performance XSL-FO rendering for variable data printing
High volume print jobs are getting more common due to the growing demand for personalized documents. In this context, Variable Data Printing (VDP) has become a useful tool for mar...
Fabio Giannetti, Luiz Gustavo Fernandes, Rogerio T...
SIGIR
2004
ACM
14 years 1 months ago
GaP: a factor model for discrete data
We present a probabilistic model for a document corpus that combines many of the desirable features of previous models. The model is called “GaP” for Gamma-Poisson, the distri...
John F. Canny
SDM
2007
SIAM
152views Data Mining» more  SDM 2007»
13 years 9 months ago
HP2PC: Scalable Hierarchically-Distributed Peer-to-Peer Clustering
In distributed data mining models, adopting a flat node distribution model can affect scalability. To address the problem of modularity, flexibility and scalability, we propose...
Khaled M. Hammouda, Mohamed S. Kamel