首页> 外文会议>IEEE International Conference on Healthcare Informatics >Deep Learning Model for Classifying Drug Abuse Risk Behavior in Tweets
【24h】

Deep Learning Model for Classifying Drug Abuse Risk Behavior in Tweets

机译:在推文中对药物滥用风险行为进行分类的深度学习模型

获取原文

摘要

Social media such as Twitter can provide urgently needed drug abuse intelligence to support the campaign of fighting against the national drug abuse crisis. We employed a targeted tweet collection approach and a two-staged annotation strategy that combines conventional annotation with crowdsourced annotation to produce annotated training dataset. In this demo, we share deep learning models trained in a boosting manner using the data from the two-staged annotation method and unlabeled data collection to detect drug abuse risk behavior in tweets.
机译:Twitter之类的社交媒体可以提供急需的吸毒情报,以支持抗击全国性吸毒危机的运动。我们采用了针对性的推文收集方法和两阶段注释策略,该策略将常规注释与众包注释相结合以生成带注释的训练数据集。在此演示中,我们共享使用两阶段注释方法中的数据和未标记的数据收集以提升方式训练的深度学习模型,以检测推文中的药物滥用风险行为。

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