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Latent Dirichlet allocation

Known as: LDA 
In natural language processing, latent Dirichlet allocation (LDA) is a generative statistical model that allows sets of observations to be explained… Expand
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Papers overview

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Highly Cited
2011
Highly Cited
2011
We introduce hierarchically supervised latent Dirichlet allocation (HSLDA), a model for hierarchically and multiply labeled bag… Expand
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Highly Cited
2010
Highly Cited
2010
We develop an online variational Bayes (VB) algorithm for Latent Dirichlet Allocation (LDA). Online LDA is based on online… Expand
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Highly Cited
2010
Highly Cited
2010
It is important to identify the “correct” number of topics in mechanisms like Latent Dirichlet Allocation(LDA) as they determine… Expand
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Highly Cited
2010
Highly Cited
2010
We propose fLDA, a novel matrix factorization method to predict ratings in recommender system applications where a "bag-of-words… Expand
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Highly Cited
2009
Highly Cited
2009
Tagging systems have become major infrastructures on the Web. They allow users to create tags that annotate and categorize… Expand
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Highly Cited
2009
Highly Cited
2009
Inference algorithms for topic models are typically designed to be run over an entire collection of documents after they have… Expand
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Highly Cited
2008
Highly Cited
2008
In this paper we introduce a novel collapsed Gibbs sampling method for the widely used latent Dirichlet allocation (LDA) model… Expand
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Highly Cited
2007
Highly Cited
2007
In recent years, the language model Latent Dirichlet Allocation (LDA), which clusters co-occurring words into topics, has been… Expand
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Highly Cited
2006
Highly Cited
2006
Latent Dirichlet allocation (LDA) is a Bayesian network that has recently gained much popularity in applications ranging from… Expand
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Highly Cited
2003
Highly Cited
2003
We propose a generative model for text and other collections of discrete data that generalizes or improves on several previous… Expand
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