TGB at SemEval-2016 Task 5: Multi-Lingual Constraint System for Aspect Based Sentiment Analysis

Abstract

This paper gives the description of the TGB system submitted to the Aspect Based Sentiment Analysis Task of SemEval-2016 (Task 5). The system is built on linear binary classifiers for aspect category classification (Slot 1), on lexicon-based detection for opinion target expressions extraction (Slot 2), and on linear multi-class classifiers for sentiment polarity detection (Slot 3). We conducted several different approaches for feature selection to improve classification performance on both Slot 1 and Slot 3. Our proposed methods are easily adaptable to all languages and domains since they are built as constrained systems which do not use any additional resources other than the provided datasets and which uses standard preprocessing methods.