Learning Document Embeddings by Predicting N-grams for Sentiment Classification of Long Movie Reviews
Table 3: Comparison of DV-ngram with bag-of-ngram baseline.
['[BOLD] Model', '[BOLD] Unigram', '[BOLD] Bigram', '[BOLD] Trigram']
This results also suggests that the performance of DV-ngram can be further improved by adding more unlabeled sentiment related documents. Note that some other models are inherently unable to make use of this additional data such as the bag-of-ngram methods in this table. The best performance is achieved by DV-tri, for simplicity, we will report only the result of DV-tri in following experiments.