Latent dirichlet allocation
Citations
723 citations
Cites background or methods from "Latent dirichlet allocation"
...The LDA model is learned via Gibbs sampling....
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...Extending from LSA, probabilistic topic models such as probabilistic LSA (PLSA), Latent Dirichlet Allocation (LDA), and Bi-Lingual Topic Model (BLTM), have been proposed and successfully applied to semantic matching [19][4][16][15][39]....
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...LDA gives slightly better results than the PLSA, and LDA with 500 topics significantly outperforms BM25 and ULM....
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...We see that using clickthrough data for model training leads to improvement over PLSA and LDA....
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...LDA (Row 5 and 6) is our implementation of the model in [39]....
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720 citations
Cites methods from "Latent dirichlet allocation"
...One of the earliest published dual translation systems used a technique known as latent semantic indexing (LSI) [Blei et al. 2003; Landauer et al. 1998]....
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...Concrete implementations of the ESA model have recently produced results comparable with LSI-based systems [Cimiano et al. 2009; Anderka et al. 2009]....
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...Latent semantic indexing (LSI) and TREC-2....
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...Latent Dirichlet allocation (LDA) [Blei et al. 2003], a probabilistic technique analogous to latent semantic analysis, suffers from the same problems as LSI [Cimiano et al. 2009]....
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...One of the earliest published dual translation systems used a technique known as latent semantic indexing (LSI) [Blei et al. 2003; Landauer et al. 1998]....
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716 citations
710 citations
Cites background from "Latent dirichlet allocation"
...Long et al. (2011) return the k most relevant and diverse posts to capture the event context based on cosine similarity between posts within a given time interval, while Cordeiro (2012) returns the set of hashtags related to the events based on an LDA topic model....
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...Finally, when an event is detected within a given time interval, LDA is applied to all tweets related to the hashtag in each corresponding time series to extract a set of latent topics, which provide an improved summary of event description....
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...Similarly, Cordeiro (2012) proposed a continuous wavelet transformation based on hashtag occurrences combined with a topic model inference using latent Dirichlet allocation (LDA) (Blei et al. 2003)....
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707 citations
References
17,608 citations
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