Phonetic-enriched Text Representationfor Chinese Sentiment Analysiswith Reinforcement Learning
TABLE IX: Cross-domain evaluation. Datasets on the first column are the training sets. Datasets on the first row are the testing sets. The second column represents various baselines and our proposed method.
['Weibo', 'Hsentic', 'Weibo -', 'It168 66.47', 'Chn2000 61.84', 'Review-4 64.93', 'Review-5 63.71']
In this section, we examine how our model performs across different domains and datasets in order to validate the generalizability of our proposed method. Particularly for our model, we firstly pretrain the LSTM critic network on the training set. Then we fix the parameters of critic network and train the policy network on the same training set. Next, we co-train the LSTM critic network and policy network for 30 epochs. For other baselines, an LSTM network is trained using the same training set. By the end of each epoch, the development set of this training dataset and the other four datasets are tested. The epoch results are recorded. In the end, the testing result of the epoch which has the best development result are reported.