Abstract
This paper reports on our participation in SemEval-2015 Task 12, which was devoted to Aspect-Based Sentiment Analysis. Participants were required to identify the category (entity and attribute), the opinion target, and the polarity of customer reviews. The system we built relies on classification algorithms to identify aspect categories and on a set of rules to identify the opinion target. We propose a two-phase classification approach for category identification and use a simple method for polarity detection. Our results outperform the baseline in many cases, which means our system could be used as an alternative for aspect classification.
Cite
CITATION STYLE
Kauer, A., & Moreira, V. P. (2015). UFRGS: Identifying Categories and Targets in Customer Reviews. In SemEval 2015 - 9th International Workshop on Semantic Evaluation, co-located with the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2015 - Proceedings (pp. 725–729). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s15-2123
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
