Aspects Extraction for Aspect Level Opinion Analysis Based on Deep CNN

摘要

Extracting aspect term is essential for aspect level sentiment analysis; Sentiment analysis collects and extracts the opinions expressed in social media and websites' comments and then analyzes them, helping users and stakeholders understand public views on the issues raised better and more quickly. Aspect-level sentiment analysis provides more detailed information, which is very beneficial for use in many various domains. In this paper, the significant contribution is to provide a data preprocessing method and a deep convolutional neural network (CNN) to label each word in opinionated sentences as an aspect or non-aspect word. The proposed method extracts the terms of the aspect that can be used in analyzing the sentiment of the expressed aspect terms in the comments and opinions. The experimental results of the proposed method performed on the SemEval-2014 dataset show that it performs better than other prominent methods such as deep CNN. The proposed data preprocessing method with the deep CNN network can improve extraction of aspect terms according to F-measure by at least 1.05% and 0.95% on restaurant and laptop domains.