Latent Dirichlet allocation
Probability model / From Wikipedia, the free encyclopedia
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Not to be confused with linear discriminant analysis.
In natural language processing, latent Dirichlet allocation (LDA) is a Bayesian network (and, therefore, a generative statistical model) for modeling automatically extracted topics in textual corpora. The LDA is an example of a Bayesian topic model. In this, observations (e.g., words) are collected into documents, and each word's presence is attributable to one of the document's topics. Each document will contain a small number of topics.
This article may be too technical for most readers to understand. (August 2017) |