Latent Dirichlet Allocation (LDA) is an unsupervised machine learning algorithm for topic modeling, meaning identifying sets of words that characterize topics that might not be obvious—they are ...

The LDA topic modeling algorithm was developed in 2003 and has been widely used for academic research and for commercial applications, like search engines.