Hi.,

In machine learning and natural language processing, a topic model is a type of statistical model for discovering the abstract "topics" that occur in a collection of documents. Topic modeling is a frequently used text-mining tool for discovery of hidden semantic structures in a text body.

In natural language processing, latent Dirichlet allocation (LDA) is a generative statistical model that allows sets of observations to be explained by unobserved groups that explain why some parts of the data are similar. ... LDA is an example of a topic model.

For more info:

https://ourcodingclub.github.io/2018/12/10/topic-modelling-python.html

I'm only aware of a C implementation of correlated topic models by David Blei, which can be found here: https://github.com/blei-lab/ctm-c

Thank you for the suggestion, Richard!