For short-text classification we use the Stanford sentiment treebank (TR) 3 , customer reviews dataset (CR) (Hu and Liu, 2004), subjective dataset (SUBJ) (Pang and Lee, 2004) and movie reviews (MR) (Pang and Lee, 2005).
to address the feature sparseness problem encountered in short-text and cross-domain classification tasks, we propose a novel method that computes related features that can be appended to the feature vectors to reduce the sparsity.