Then we introduce scalable implementations of the Rectified Anchor Word (RAW) algorithm and various evaluation metrics, investigating the impact of each inference step from vocabulary curation to topic inference.
then the main learning task of topic models is to find the wordtopic matrix B and topic-document matrix W that approximates H ≈ BW with the column-stochastic constraints B ∈ CS N ×K , W ∈ CS K×M .