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Topic modeling.
It's a field called probabilistic topic modeling.
Bravo González-Blas, C. et al. cisTopic: cis-regulatory topic modeling on single-cell ATAC-seq data.
We used topic modeling to synthesize the "topics" from 1540 comments.
Content analysis, a widely-applied social science research method, is increasingly being supplemented by topic modeling.
I will first briefly review scalable probabilistic topic modeling with stochastic variational inference.
We show its efficiency through two categories of EM applications, clustering and topic modeling.
In summary, this article encompasses the current research in multilingual probabilistic topic modeling.
"Latent topic modeling for text analysis" presents methodological details underlying non-negative matrix factorization as a method for topic modeling (Lee and Seung 1999).
"We're using a non-semantic neural topic modeling approach with a heuristic function for hierarchy building," says Schjøll Brede.
Text-based topic modeling typically reveals that any one document is a mixture of different topics.
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