Paper: UWB: Machine Learning Approach to Aspect-Based Sentiment Analysis

ACL ID S14-2145
Title UWB: Machine Learning Approach to Aspect-Based Sentiment Analysis
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2014
Authors

This paper describes our system partici- pating in the aspect-based sentiment anal- ysis task of Semeval 2014. The goal was to identify the aspects of given tar- get entities and the sentiment expressed to- wards each aspect. We firstly introduce a system based on supervised machine learning, which is strictly constrained and uses the training data as the only source of information. This system is then ex- tended by unsupervised methods for latent semantics discovery (LDA and semantic spaces) as well as the approach based on sentiment vocabularies. The evaluation was done on two domains, restaurants and laptops. We show that our approach leads to very promising results.