Amobee at SemEval-2018 Task 1: GRU Neural Network with a CNN Attention Mechanism for Sentiment Classification
Abstract
This paper describes the participation of Amobee in the shared sentiment analysis task at SemEval 2018. We participated in all the English sub-tasks and the Spanish valence tasks. Our system consists of three parts: training task-specific word embeddings, training a model consisting of gated-recurrent-units (GRU) with a convolution neural network (CNN) attention mechanism and training stacking-based ensembles for each of the sub-tasks. Our algorithm reached the 3rd and 1st places in the valence ordinal classification sub-tasks in English and Spanish, respectively.- Anthology ID:
- S18-1033
- Volume:
- Proceedings of the 12th International Workshop on Semantic Evaluation
- Month:
- June
- Year:
- 2018
- Address:
- New Orleans, Louisiana
- Editors:
- Marianna Apidianaki, Saif M. Mohammad, Jonathan May, Ekaterina Shutova, Steven Bethard, Marine Carpuat
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 218–225
- Language:
- URL:
- https://aclanthology.org/S18-1033
- DOI:
- 10.18653/v1/S18-1033
- Cite (ACL):
- Alon Rozental and Daniel Fleischer. 2018. Amobee at SemEval-2018 Task 1: GRU Neural Network with a CNN Attention Mechanism for Sentiment Classification. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 218–225, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- Amobee at SemEval-2018 Task 1: GRU Neural Network with a CNN Attention Mechanism for Sentiment Classification (Rozental & Fleischer, SemEval 2018)
- PDF:
- https://preview.aclanthology.org/teach-a-man-to-fish/S18-1033.pdf