首页> 外文会议>Annual conference of the North American Chapter of the Association for Computational Linguistics: human language technologies;International workshop on semantic evaluation >LaSTUS/TALN at SemEval-2019 Task 6: Identification and Categorization of Offensive Language in Social Media with Attention-based Bi-LSTM model
【24h】

LaSTUS/TALN at SemEval-2019 Task 6: Identification and Categorization of Offensive Language in Social Media with Attention-based Bi-LSTM model

机译:LaSTUS / TALN在SemEval-2019上的任务6:使用基于注意的Bi-LSTM模型识别和分类社交媒体中的攻击性语言

获取原文

摘要

This paper describes a bidirectional Long-Short Term Memory network for identifying offensive language in Twitter. Our system has been developed in the context of the SemEval 2019 Task 6 which comprises three different sub-tasks, namely A: Offensive Language Detection, B: Categorization of Offensive Language, C: Offensive Language Target Identification. We used a pre-trained Word Embeddings in tweet data, including information about emojis and hashtags. Our approach achieves good performance in the three sub-tasks.
机译:本文介绍了一种双向的“长期-短期记忆”网络,用于识别Twitter中的冒犯性语言。我们的系统是在SemEval 2019任务6的上下文中开发的,该任务包含三个不同的子任务,即A:攻击性语言检测,B:攻击性语言分类,C:攻击性语言目标识别。我们在推特数据中使用了预训练的单词嵌入,包括有关表情符号和主题标签的信息。我们的方法在三个子任务中均取得了良好的性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号