Paper: UNITOR: Aspect Based Sentiment Analysis with Structured Learning

ACL ID S14-2135
Title UNITOR: Aspect Based Sentiment Analysis with Structured Learning
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2014
Authors

In this paper, the UNITOR system partici- pating in the SemEval-2014 Aspect Based Sentiment Analysis competition is pre- sented. The task is tackled exploiting Ker- nel Methods within the Support Vector Machine framework. The Aspect Term Extraction is modeled as a sequential tag- ging task, tackled through SVM hmm . The Aspect Term Polarity, Aspect Category and Aspect Category Polarity detection are tackled as a classification problem where multiple kernels are linearly combined to generalize several linguistic information. In the challenge, UNITOR system achieves good results, scoring in almost all rank- ings between the 2 nd and the 8 th position within about 30 competitors.