@inproceedings{zhou-etal-2019-ynu,
title = "{YNU}-{HPCC} at {S}em{E}val-2019 Task 6: Identifying and Categorising Offensive Language on {T}witter",
author = "Zhou, Chengjin 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/S19-2142",
doi = "10.18653/v1/S19-2142",
pages = "812--817",
abstract = "This document describes the submission of team YNU-HPCC to SemEval-2019 for three Sub-tasks of Task 6: Sub-task A, Sub-task B, and Sub-task C. We have submitted four systems to identify and categorise offensive language. The first subsystem is an attention-based 2-layer bidirectional long short-term memory (BiLSTM). The second subsystem is a voting ensemble of four different deep learning architectures. The third subsystem is a stacking ensemble of four different deep learning architectures. Finally, the fourth subsystem is a bidirectional encoder representations from transformers (BERT) model. Among our models, in Sub-task A, our first subsystem performed the best, ranking 16th among 103 teams; in Sub-task B, the second subsystem performed the best, ranking 12th among 75 teams; in Sub-task C, the fourth subsystem performed best, ranking 4th among 65 teams.",
}
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%0 Conference Proceedings
%T YNU-HPCC at SemEval-2019 Task 6: Identifying and Categorising Offensive Language on Twitter
%A Zhou, Chengjin
%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 zhou-etal-2019-ynu
%X This document describes the submission of team YNU-HPCC to SemEval-2019 for three Sub-tasks of Task 6: Sub-task A, Sub-task B, and Sub-task C. We have submitted four systems to identify and categorise offensive language. The first subsystem is an attention-based 2-layer bidirectional long short-term memory (BiLSTM). The second subsystem is a voting ensemble of four different deep learning architectures. The third subsystem is a stacking ensemble of four different deep learning architectures. Finally, the fourth subsystem is a bidirectional encoder representations from transformers (BERT) model. Among our models, in Sub-task A, our first subsystem performed the best, ranking 16th among 103 teams; in Sub-task B, the second subsystem performed the best, ranking 12th among 75 teams; in Sub-task C, the fourth subsystem performed best, ranking 4th among 65 teams.
%R 10.18653/v1/S19-2142
%U https://aclanthology.org/S19-2142
%U https://doi.org/10.18653/v1/S19-2142
%P 812-817
Markdown (Informal)
[YNU-HPCC at SemEval-2019 Task 6: Identifying and Categorising Offensive Language on Twitter](https://aclanthology.org/S19-2142) (Zhou et al., SemEval 2019)
ACL