Aspect Category Detection in Product Reviews using Contextual Representation
Aspect category detection (ACD) is one of the challenging subtasks in aspect based sentiment analysis. The goal of this task is to detect implicit or explicit aspect categories from the sentences of user generated reviews. Since annotation over the aspects is timeconsuming, the amount of labeled data is limited for supervised learning. In this paper, we study contextual representations of text segments in the reviews using the BERT model to better extract useful features from them, and train a supervised classifier with a small amount of labeled data for the ACD task. Experimental results obtained on Amazon reviews of six product domains show that our method is effective in some domains.