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… (More)
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Papers overview

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2014
2014
Latent Dirichlet allocation(LDA) is a generative topic model to find latent topics in a text corpus. It can be trained via… (More)
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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… (More)
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2011
2011
Understanding how topics within a document evolve over the structure of the document is an interesting and potentially important… (More)
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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… (More)
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Highly Cited
2010
Highly Cited
2010
0950-5849/$ see front matter 2010 Elsevier B.V. A doi:10.1016/j.infsof.2010.04.002 * Corresponding author. Tel.: +1 256 824 6088… (More)
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Highly Cited
2009
Highly Cited
2009
Latent Dirichlet Allocation (LDA) is an unsupervised, statistical approach to document modeling that discovers latent semantic… (More)
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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… (More)
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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… (More)
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Highly Cited
2007
Highly Cited
2007
We investigate the problem of learning a widely-used latent-variable model – the Latent Dirichlet Allocation (LDA) or “topic… (More)
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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… (More)
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