MainiwayAI at IJCNLP-2017 Task 2: Ensembles of Deep Architectures for Valence-Arousal Prediction
Yassine Benajiba, Jin Sun, Yong Zhang, Zhiliang Weng, Or Biran
Abstract
This paper introduces Mainiway AI Labs submitted system for the IJCNLP 2017 shared task on Dimensional Sentiment Analysis of Chinese Phrases (DSAP), and related experiments. Our approach consists of deep neural networks with various architectures, and our best system is a voted ensemble of networks. We achieve a Mean Absolute Error of 0.64 in valence prediction and 0.68 in arousal prediction on the test set, both placing us as the 5th ranked team in the competition.- Anthology ID:
- I17-4019
- Volume:
- Proceedings of the IJCNLP 2017, Shared Tasks
- Month:
- December
- Year:
- 2017
- Address:
- Taipei, Taiwan
- Editors:
- Chao-Hong Liu, Preslav Nakov, Nianwen Xue
- Venue:
- IJCNLP
- SIG:
- Publisher:
- Asian Federation of Natural Language Processing
- Note:
- Pages:
- 118–123
- Language:
- URL:
- https://aclanthology.org/I17-4019
- DOI:
- Cite (ACL):
- Yassine Benajiba, Jin Sun, Yong Zhang, Zhiliang Weng, and Or Biran. 2017. MainiwayAI at IJCNLP-2017 Task 2: Ensembles of Deep Architectures for Valence-Arousal Prediction. In Proceedings of the IJCNLP 2017, Shared Tasks, pages 118–123, Taipei, Taiwan. Asian Federation of Natural Language Processing.
- Cite (Informal):
- MainiwayAI at IJCNLP-2017 Task 2: Ensembles of Deep Architectures for Valence-Arousal Prediction (Benajiba et al., IJCNLP 2017)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/I17-4019.pdf