Abstract
In this paper, we present the system we have developed for the SemEval-2014 Task 4 dedicated to Aspect-Based Sentiment Analysis. The system is based on a robust parser that provides information to feed different classifiers with linguistic features dedicated to aspect categories and aspect categories polarity classification. We mainly present the work which has been done on the restaurant domain1 for the four subtasks, aspect term and category detection and aspect term and category polarity.
Cite
CITATION STYLE
Brun, C., Popa, D. N., & Roux, C. (2014). XRCE: Hybrid Classification for Aspect-based Sentiment Analysis. In 8th International Workshop on Semantic Evaluation, SemEval 2014 - co-located with the 25th International Conference on Computational Linguistics, COLING 2014, Proceedings (pp. 838–842). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/s14-2149
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
