Latent Dirichlet allocation (LDA) extends pLSA by adding a generative process for topics.

It is the most popular topic model because it tends to produce meaningful topics that humans can relate to, can assign topics to new documents, and is extensible. Variants of LDA models can include metadata such as authors, or image data, or learn hierarchical topics.