AUEB-ABSA

This is the software that accompanies the paper "AUEB-ABSA at SemEval-2016 Task 5: Supervised Machine Learning for Aspect Based Sentiment Analysis" by Dionysios Xenos, Panagiotis Theodorakakos, John Pavlopoulos, Prodromos Malakasiotis and Ion Androutsopoulos. The paper describes our submissions to the Aspect Based Sentiment Analysis task of SemEval-2016. For Aspect Category Detection (Subtask1/Slot1), we used multiple ensembles, based on Support Vector Machine classifiers. For Opinion Target Expression extraction (Subtask1/Slot2), we used a sequence labeling approach with Conditional Random Fields. For Polarity Detection (Subtask1/Slot3), we used an ensemble of two supervised classifiers, one based on hand crafted features and one based on word embeddings. Our systems were ranked in the top 6 positions in all the tasks we participated.