Adversarial Training Based Multi-Source Unsupervised Domain Adaptationfor Sentiment Analysis
Table 2: Results on Amazon review dataset. The highest domain performance is shown in bold. The numbers in brackets represent the improvements relative to the best performance in the above baselines. Except for our model, the rest is taken from [Chen and Cardie2018].
['Target Domain', 'Book', 'DVD', 'Elec.', 'Kit', 'Avg']
It shows that our second framework outperforms the state of art by 1.42 percentage. But for the first framework, we just obtain a comparable average result. For this, we argue the reason is that we can not adopt strong source extractors, the integrated results will also be weak. It is worthwhile noting that all the baselines are just for one target domain, but our framework can deal with multiple target domains.