Model that extracts hidden semantic structures from large volumes of text.
- Groups words together into topics
- Uses Gensim, which deploys memory-independent algorithms w.r.t. the corpus size (can process input larger than RAM, streamed, out-of-core)
- Uses Latent Dirichlet Allocation (LDA) to induce probabilistic topics