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ICDM
2008
IEEE
80views Data Mining» more  ICDM 2008»
13 years 11 months ago
Collective Latent Dirichlet Allocation
In this paper, we propose a new variant of Latent Dirichlet Allocation(LDA): Collective LDA (C-LDA), for multiple corpora modeling. C-LDA combines multiple corpora during learning...
Zhiyong Shen, Jun Sun, Yi-Dong Shen
ECIR
2009
Springer
14 years 1 months ago
Topic and Trend Detection in Text Collections Using Latent Dirichlet Allocation
Algorithms that enable the process of automatically mining distinct topics in document collections have become increasingly important due to their applications in many fields and ...
Levent Bolelli, Seyda Ertekin, C. Lee Giles
NIPS
2001
13 years 6 months ago
Latent Dirichlet Allocation
We describe latent Dirichlet allocation (LDA), a generative probabilistic model for collections of discrete data such as text corpora. LDA is a three-level hierarchical Bayesian m...
David M. Blei, Andrew Y. Ng, Michael I. Jordan
NIPS
2007
13 years 6 months ago
Spatial Latent Dirichlet Allocation
In recent years, the language model Latent Dirichlet Allocation (LDA), which clusters co-occurring words into topics, has been widely applied in the computer vision field. Howeve...
Xiaogang Wang, Eric Grimson
SLSFS
2005
Springer
13 years 10 months ago
Discrete Component Analysis
Abstract. This article presents a unified theory for analysis of components in discrete data, and compares the methods with techniques such as independent component analysis, non-...
Wray L. Buntine, Aleks Jakulin