Unsupervised Machine Commenting with Neural Variational Topic Model
Table 3: The performance of the unsupervised models and supervised models under the generative evaluation settings. (METEOR, ROUGE, CIDEr, BLEU: higher is better.)
['[EMPTY]', '[BOLD] Model', '[BOLD] Paired', '[BOLD] Unpaired', '[BOLD] METEOR', '[BOLD] ROUGE', '[BOLD] CIDEr', '[BOLD] BLEU']
Similar to the retrieval evaluation, our proposed model outperforms the other unsupervised methods, which are TF-IDF, NVDM, and LDA, in generative evaluation. Still, the supervised IR achieves better scores than the seq2seq model. With the help of our proposed model, both IR and S2S achieve an improvement under the semi-supervised scenarios.