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        <title>YNUWB at SemEval-2019 Task 6: K-max pooling CNN with average meta-embedding for identifying offensive language</title>
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    <abstract>This paper describes the system submitted to SemEval 2019 Task 6: OffensEval 2019. The task aims to identify and categorize offensive language in social media, we only participate in Sub-task A, which aims to identify offensive language. In order to address this task, we propose a system based on a K-max pooling convolutional neural network model, and use an argument for averaging as a valid meta-embedding technique to get a metaembedding. Finally, we also use a cyclic learning rate policy to improve model performance. Our model achieves a Macro F1-score of 0.802 (ranked 9/103) in the Sub-task A.</abstract>
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%0 Conference Proceedings
%T YNUWB at SemEval-2019 Task 6: K-max pooling CNN with average meta-embedding for identifying offensive language
%A Wang, Bin
%A Zhou, Xiaobing
%A Zhang, Xuejie
%S Proceedings of the 13th International Workshop on Semantic Evaluation
%D 2019
%8 jun
%I Association for Computational Linguistics
%C Minneapolis, Minnesota, USA
%F wang-etal-2019-ynuwb
%X This paper describes the system submitted to SemEval 2019 Task 6: OffensEval 2019. The task aims to identify and categorize offensive language in social media, we only participate in Sub-task A, which aims to identify offensive language. In order to address this task, we propose a system based on a K-max pooling convolutional neural network model, and use an argument for averaging as a valid meta-embedding technique to get a metaembedding. Finally, we also use a cyclic learning rate policy to improve model performance. Our model achieves a Macro F1-score of 0.802 (ranked 9/103) in the Sub-task A.
%R 10.18653/v1/S19-2143
%U https://aclanthology.org/S19-2143
%U https://doi.org/10.18653/v1/S19-2143
%P 818-822

Markdown (Informal)

[YNUWB at SemEval-2019 Task 6: K-max pooling CNN with average meta-embedding for identifying offensive language](https://aclanthology.org/S19-2143) (Wang et al., SemEval 2019)

• YNUWB at SemEval-2019 Task 6: K-max pooling CNN with average meta-embedding for identifying offensive language (Wang et al., SemEval 2019)

ACL

• Bin Wang, Xiaobing Zhou, and Xuejie Zhang. 2019. YNUWB at SemEval-2019 Task 6: K-max pooling CNN with average meta-embedding for identifying offensive language. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 818–822, Minneapolis, Minnesota, USA. Association for Computational Linguistics.