首页> 外文会议>BioNLP shared task 2013 >Overview of the Cancer Genetics (CG) task of BioNLP Shared Task 2013
【24h】

Overview of the Cancer Genetics (CG) task of BioNLP Shared Task 2013

机译:BioNLP共享任务2013的癌症遗传学(CG)任务概述

获取原文
获取原文并翻译 | 示例

摘要

We present the design, preparation, results and analysis of the Cancer Genetics (CG) event extraction task, a main task of the BioNLP Shared Task (ST) 2013. The CG task is an information extraction task targeting the recognition of events in text, represented as structured n-ary associations of given physical entities. In addition to addressing the cancer domain, the CG task is differentiated from previous event extraction tasks in the BioNLP ST series in addressing a wide range of pathological processes and multiple levels of biological organization, ranging from the molecular through the cellular and organ levels up to whole organisms. Final test set submissions were accepted from six teams. The highest-performing system achieved an F-score of 55.4%. This level of performance is broadly comparable with the state of the art for established molecular-level extraction tasks, demonstrating that event extraction resources and methods generalize well to higher levels of biological organization and are applicable to the analysis of scientific texts on cancer.
机译:我们介绍了癌症遗传学(CG)事件提取任务的设计,准备,结果和分析,这是BioNLP共享任务(ST)2013的主要任务。CG任务是针对文本中事件识别的信息提取任务,表示为给定物理实体的结构化n元关联。除了解决癌症领域外,CG任务还与BioNLP ST系列中以前的事件提取任务不同,可解决广泛的病理过程和生物组织的多个层次,从分子水平到细胞和器官水平直至整个生物。最终的测试集提交被六个团队接受。绩效最高的系统的F得分为55.4%。对于已建立的分子水平提取任务,这种性能水平与现有技术大致相当,这表明事件提取资源和方法可以很好地推广到更高水平的生物组织,并且适用于分析癌症的科学文献。

著录项

  • 来源
    《BioNLP shared task 2013》|2013年|58-66|共9页
  • 会议地点 Sofia(BG)
  • 作者单位

    National Centre for Text Mining and School of Computer Science, University of Manchester;

    National Centre for Text Mining and School of Computer Science, University of Manchester;

    National Centre for Text Mining and School of Computer Science, University of Manchester;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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