Multi-Domain Aspect Extraction using Support Vector Machines

Multi-Domain Aspect Extraction using Support Vector Machines

This paper describes a system to extract aspect categories for the task of aspect based sentiment analysis. This system can extract both implicit and explicit aspects. We propose a one-vs-rest Support Vector Machine (SVM) classifier preceded by a state of the art preprocessing pipeline. We present the use of mean embeddings as a feature along with two other new features to significantly improve the accuracy of the SVM classifier. This solution is extensible to customer reviews in different domains. Our results outperform the best recorded F1 score in the SemEval-2016 Task 5 dataset consisting of customer reviews from restaurant and laptop domains.