Latent dirichlet allocation
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175 citations
175 citations
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Cites methods from "Latent dirichlet allocation"
...This can be addressed by topic models such as Latent Dirichlet Allocation (LDA) [6]....
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...This is Figure 4: Synchronization during a sampling cycle. collapsing ft also introduces coupling across users, however we deal with that using the architecture of [23]. tt Sampling zij : The conditional probability for zij has the same structure as in LDA albeit with the previously de.ned compound prior....
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...Due to the large scale of this dataset, we can not apply batch LDA directly over it....
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...Instead, we sampled 2M users from the training set and built a static LDA model over them....
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...LDA was introduced by [6] for the purpose of document modeling....
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References
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"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