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One key task of fine-grained sentiment analysis of product reviews is toextract product aspects or features that users have expressed opinions on. Thispaper focuses on supervised aspect extraction using deep learning. Unlike otherhighly sophisticated supervised deep learning models, this paper proposes anovel and yet simple CNN model employing two types of pre-trained embeddingsfor aspect extraction: general-purpose embeddings and domain-specificembeddings. Without using any additional supervision, this model achievessurprisingly good results, outperforming state-of-the-art sophisticatedexisting methods. To our knowledge, this paper is the first to report suchdouble embeddings based CNN model for aspect extraction and achieve very goodresults.

Double Embeddings and CNN-based Sequence Labeling for Aspect Extraction