@inproceedings{ding-etal-2019-ynu-dyx,
title = "{YNU}{\_}{DYX} at {S}em{E}val-2019 Task 9: A Stacked {B}i{LSTM} for Suggestion Mining Classification",
author = "Ding, Yunxia and
Zhou, Xiaobing and
Zhang, Xuejie",
editor = "May, Jonathan and
Shutova, Ekaterina and
Herbelot, Aurelie and
Zhu, Xiaodan and
Apidianaki, Marianna and
Mohammad, Saif M.",
booktitle = "Proceedings of the 13th International Workshop on Semantic Evaluation",
month = jun,
year = "2019",
address = "Minneapolis, Minnesota, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S19-2223",
doi = "10.18653/v1/S19-2223",
pages = "1272--1276",
abstract = "In this paper we describe a deep-learning system that competed as SemEval 2019 Task 9-SubTask A: Suggestion Mining from Online Reviews and Forums. We use Word2Vec to learn the distributed representations from sentences. This system is composed of a Stacked Bidirectional Long-Short Memory Network (SBiLSTM) for enriching word representations before and after the sequence relationship with context. We perform an ensemble to improve the effectiveness of our model. Our official submission results achieve an F1-score 0.5659.",
}
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<abstract>In this paper we describe a deep-learning system that competed as SemEval 2019 Task 9-SubTask A: Suggestion Mining from Online Reviews and Forums. We use Word2Vec to learn the distributed representations from sentences. This system is composed of a Stacked Bidirectional Long-Short Memory Network (SBiLSTM) for enriching word representations before and after the sequence relationship with context. We perform an ensemble to improve the effectiveness of our model. Our official submission results achieve an F1-score 0.5659.</abstract>
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%0 Conference Proceedings
%T YNU_DYX at SemEval-2019 Task 9: A Stacked BiLSTM for Suggestion Mining Classification
%A Ding, Yunxia
%A Zhou, Xiaobing
%A Zhang, Xuejie
%Y May, Jonathan
%Y Shutova, Ekaterina
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%S Proceedings of the 13th International Workshop on Semantic Evaluation
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, Minnesota, USA
%F ding-etal-2019-ynu-dyx
%X In this paper we describe a deep-learning system that competed as SemEval 2019 Task 9-SubTask A: Suggestion Mining from Online Reviews and Forums. We use Word2Vec to learn the distributed representations from sentences. This system is composed of a Stacked Bidirectional Long-Short Memory Network (SBiLSTM) for enriching word representations before and after the sequence relationship with context. We perform an ensemble to improve the effectiveness of our model. Our official submission results achieve an F1-score 0.5659.
%R 10.18653/v1/S19-2223
%U https://aclanthology.org/S19-2223
%U https://doi.org/10.18653/v1/S19-2223
%P 1272-1276
Markdown (Informal)
[YNU_DYX at SemEval-2019 Task 9: A Stacked BiLSTM for Suggestion Mining Classification](https://aclanthology.org/S19-2223) (Ding et al., SemEval 2019)
ACL