Leveraging Structural and Semantic Correspondence for Attribute-Oriented Aspect Sentiment Discovery
Table 5: Accuracy and AUC of sentiment classification on hotel reviews.
['[EMPTY]', 'T=20 Acc', 'T=20 AUC', 'T=40 Acc', 'T=40 AUC', 'T=60 Acc', 'T=60 AUC']
AATS achieves better accuracy but worse AUC scores than JST. ASUM yields better accuracy and comparable AUC scores compared with JST. Trait consistently outperforms all baseline models given different aspect numbers with an average gain in accuracy of 3%. Incorporating attributes and structural and semantic correspondence into conditional probability distributions greatly benefit the model in capturing dependencies among attributes, aspects, and sentiments.