@inproceedings{yue-etal-2019-ynu,
title = "{YNU}-{HPCC} at {S}em{E}val-2019 Task 9: Using a {BERT} and {CNN}-{B}i{LSTM}-{GRU} Model for Suggestion Mining",
author = "Yue, Ping and
Wang, Jin 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/S19-2224",
doi = "10.18653/v1/S19-2224",
pages = "1277--1281",
abstract = "Consumer opinions towards commercial entities are generally expressed through online reviews, blogs, and discussion forums. These opinions largely express positive and negative sentiments towards a given entity,but also tend to contain suggestions for improving the entity. In this task, we extract suggestions from given the unstructured text, compared to the traditional opinion mining systems. Such suggestion mining is more applicability and extends capabilities.",
}
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%0 Conference Proceedings
%T YNU-HPCC at SemEval-2019 Task 9: Using a BERT and CNN-BiLSTM-GRU Model for Suggestion Mining
%A Yue, Ping
%A Wang, Jin
%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 yue-etal-2019-ynu
%X Consumer opinions towards commercial entities are generally expressed through online reviews, blogs, and discussion forums. These opinions largely express positive and negative sentiments towards a given entity,but also tend to contain suggestions for improving the entity. In this task, we extract suggestions from given the unstructured text, compared to the traditional opinion mining systems. Such suggestion mining is more applicability and extends capabilities.
%R 10.18653/v1/S19-2224
%U https://aclanthology.org/S19-2224
%U https://doi.org/10.18653/v1/S19-2224
%P 1277-1281
Markdown (Informal)
[YNU-HPCC at SemEval-2019 Task 9: Using a BERT and CNN-BiLSTM-GRU Model for Suggestion Mining](https://aclanthology.org/S19-2224) (Yue et al., SemEval 2019)
ACL