XJSA at SemEval-2017 Task 4: A Deep System for Sentiment Classification in Twitter

Yazhou Hao, YangYang Lan, Yufei Li, Chen Li

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Abstract
This paper describes the XJSA System submission from XJTU. Our system was created for SemEval2017 Task 4 – subtask A which is very popular and fundamental. The system is based on convolutional neural network and word embedding. We used two pre-trained word vectors and adopt a dynamic strategy for k-max pooling.
Anthology ID:
S17-2122
Volume:
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
Month:
August
Year:
2017
Address:
Vancouver, Canada
Editors:
Steven Bethard, Marine Carpuat, Marianna Apidianaki, Saif M. Mohammad, Daniel Cer, David Jurgens
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
728–731
Language:
URL:
https://aclanthology.org/S17-2122
DOI:
10.18653/v1/S17-2122
Bibkey:
Cite (ACL):
Yazhou Hao, YangYang Lan, Yufei Li, and Chen Li. 2017. XJSA at SemEval-2017 Task 4: A Deep System for Sentiment Classification in Twitter. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), pages 728–731, Vancouver, Canada. Association for Computational Linguistics.
Cite (Informal):
XJSA at SemEval-2017 Task 4: A Deep System for Sentiment Classification in Twitter (Hao et al., SemEval 2017)
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PDF:
https://preview.aclanthology.org/teach-a-man-to-fish/S17-2122.pdf
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