Abstract
This paper describes the approach developed by the ELiRF-UPV team at SemEval 2019 Task 3: Contextual Emotion Detection in Text. We have developed a Snapshot Ensemble of 1D Hierarchical Convolutional Neural Networks to extract features from 3-turn conversations in order to perform contextual emotion detection in text. This Snapshot Ensemble is obtained by averaging the models selected by a Genetic Algorithm that optimizes the evaluation measure. The proposed ensemble obtains better results than a single model and it obtains competitive and promising results on Contextual Emotion Detection in Text.
Cite
CITATION STYLE
González, J. Á., Hurtado, L. F., & Pla, F. (2019). ELiRF-UPV at SemEval-2019 task 3: Snapshot ensemble of hierarchical convolutional neural networks for contextual emotion detection. In NAACL HLT 2019 - International Workshop on Semantic Evaluation, SemEval 2019, Proceedings of the 13th Workshop (pp. 195–199). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s19-2031
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