Luke Miratrix

Prior matters: simple and general methods for evaluating and improving topic quality in topic modeling

2017 · arXiv (Cornell University)

Latent Dirichlet Allocation (LDA) models trained without stopword removal often produce topics with high posterior probabilities on uninformative words, obscuring the underlying corpus content. Even when canonical stopwords are manually removed, uninformative words common in …