Latent dirichlet allocation
Citations
1,625 citations
Cites background from "Latent dirichlet allocation"
...In the early years after 2010, based on the latent Dirichlet allocation (LDA) model [115], various supervised hierarchical feature-learning methods have been proposed in the RS community [116]–[120]....
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1,619 citations
1,600 citations
1,585 citations
1,554 citations
Cites background or methods from "Latent dirichlet allocation"
...This generative model represents each document with a mixture of topics, as in stateof-the-art approaches like Latent Dirichlet Allocation (Blei et al., 2003), and extends these approaches to author modeling by allowing the mixture weights for different topics to be determined by the authors of the…...
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...We introduce the author-topic model, a generative model for documents that extends Latent Dirichlet Allocation (LDA; Blei, Ng, & Jordan, 2003) to include authorship information....
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...A document d is a vector of Nd words, wd, where each wid is chosen from a vocabulary of size V , and a vector of Ad authors ad, chosen from a set of authors of size A....
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...Characterizing the content of documents is a standard problem addressed in information retrieval, statistical natural language processing, and machine learning....
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...…algorithms have been used to estimate the parameters of topic models, from basic expectationmaximization (EM; Hofmann, 1999), to approximate inference methods like variational EM (Blei et al., 2003), expectation propagation (Minka & Lafferty, 2002), and Gibbs sampling (Griffiths & Steyvers, 2004)....
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References
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16,079 citations
"Latent dirichlet allocation" refers background in this paper
...Finally, Griffiths and Steyvers (2002) have presented a Markov chain Monte Carlo algorithm for LDA....
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...Structures similar to that shown in Figure 1 are often studied in Bayesian statistical modeling, where they are referred to ashierarchical models(Gelman et al., 1995), or more precisely asconditionally independent hierarchical models(Kass and Steffey, 1989)....
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...Structures similar to that shown in Figure 1 are often studied in Bayesian statistical modeling, where they are referred to as hierarchical models (Gelman et al., 1995), or more precisely as conditionally independent hierarchical models (Kass and Steffey, 1989)....
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12,443 citations
"Latent dirichlet allocation" refers methods in this paper
...To address these shortcomings, IR researchers have proposed several other dimensionality reduction techniques, most notably latent semantic indexing (LSI) (Deerwester et al., 1990)....
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...To address these shortcomings, IR researchers have proposed several other dimensionality reduction techniques, most notablylatent semantic indexing (LSI)(Deerwester et al., 1990)....
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12,059 citations
"Latent dirichlet allocation" refers background or methods in this paper
...In the populartf-idf scheme (Salton and McGill, 1983), a basic vocabulary of “words” or “terms” is chosen, and, for each document in the corpus, a count is formed of the number of occurrences of each word....
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...We report results in document modeling, text classification, and collaborative filtering, comparing to a mixture of unigrams model and the probabilistic LSI model....
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7,086 citations