About: Dynamic topic model

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Within statistics, Dynamic topic models' are generative models that can be used to analyze the evolution of (unobserved) topics of a collection of documents over time. This family of models was proposed by David Blei and John Lafferty and is an extension to Latent Dirichlet Allocation (LDA) that can handle sequential documents.

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rdfs:label	Dynamic topic model (en)
rdfs:comment	Within statistics, Dynamic topic models' are generative models that can be used to analyze the evolution of (unobserved) topics of a collection of documents over time. This family of models was proposed by David Blei and John Lafferty and is an extension to Latent Dirichlet Allocation (LDA) that can handle sequential documents. (en)
dcterms:subject	Latent variable models Statistical natural language processing
Wikipage page ID	34073580 (xsd:integer)
Wikipage revision ID	1073994495 (xsd:integer)
Link from a Wikipage to another Wikipage	Multinomial distribution David Blei De Finetti's theorem Generative model Statistics Latent variable models Statistical natural language processing Latent Dirichlet allocation Exponential family Latent Dirichlet Allocation Gibbs sampling Variational methods PLSA
sameAs	Dynamic topic model Dynamic topic model Dynamic topic model Dynamic topic model
dbp:wikiPageUsesTemplate	dbt:Math dbt:Reflist
has abstract	Within statistics, Dynamic topic models' are generative models that can be used to analyze the evolution of (unobserved) topics of a collection of documents over time. This family of models was proposed by David Blei and John Lafferty and is an extension to Latent Dirichlet Allocation (LDA) that can handle sequential documents. In LDA, both the order the words appear in a document and the order the documents appear in the corpus are oblivious to the model. Whereas words are still assumed to be exchangeable, in a dynamic topic model the order of the documents plays a fundamental role. More precisely, the documents are grouped by time slice (e.g.: years) and it is assumed that the documents of each group come from a set of topics that evolved from the set of the previous slice. (en)
gold:hypernym	Models
prov:wasDerivedFrom	wikipedia-en:Dynamic_topic_model?oldid=1073994495&ns=0
page length (characters) of wiki page	5815 (xsd:nonNegativeInteger)
foaf:isPrimaryTopicOf	wikipedia-en:Dynamic_topic_model
is Link from a Wikipage to another Wikipage of	John D. Lafferty List of statistics articles Outline of machine learning
is foaf:primaryTopic of	wikipedia-en:Dynamic_topic_model

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