On one hand, a label-specific word embedding is introduced for predicting labels in SLTM according to Equation 10.
other supervised topic models for both categorical and real-valued label prediction tasks infer labels for unlabeled documents by topic distributions directly, in which, topic distributions of unlabeled documents are learned without the supervision of labels.