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相关概念视频

Introduction to Learning01:18

Introduction to Learning

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Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
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相关实验视频

Updated: Jun 28, 2025

Visualizing Motion Patterns in Acupuncture Manipulation
08:18

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Published on: July 16, 2016

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针和tuina知识图表与快速学习.

Xiaoran Li1, Xiaosong Han1, Siqing Wei1

  • 1Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry, College of Computer Science and Technology Jilin University, Changchun, China.

Frontiers in big data
|April 23, 2024
PubMed
概括

传统中医药 (TCM) 的新知识图 (KG) 改善了对针和治疗的理解. 这些结构化数据有助于提供个性化的医疗建议,并推动中医药研究.

关键词:
实体关系摘录 实体关系摘录命名实体的认可方式传统中国医药 传统中国医药知识图表知识图表快速学习 快速学习

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科学领域:

  • 计算语言学计算语言学
  • 知识表示知识表示.
  • 传统中国医学 (TCM) 是一种

背景情况:

  • 针和tuina是已建立的TCM疗法.
  • 现有的TCM治疗方案缺乏标准化和定量评估.
  • 不同的TCM系统对一致的应用提出了挑战.

研究的目的:

  • 开发一个结构化的知识基础,用于TCM针和治疗.
  • 通过数据分析实现个性化的医疗建议.
  • 解决模两可的问题,并改进TCM协议的定量评估.

主要方法:

  • 收集并处理了大量的针和图纳数据.
  • 开发了一个没有模板的中国命名实体识别 (NER) 联合培训方法 (TemplateFC),以BiLSTM和CRF层增强EntLM模型.
  • 构建了一个全面的TCM知识图 (KG),包含10,346个实体和40,919个关系.

主要成果:

  • 创建了一个强大的TCM KG,拥有多样化的实体和关系.
  • TemplateFC显著提高了中国NER的准确性,克服了实体识别和代币化问题.
  • 该KG提供了对针和tuina的见解,支持有效的信息检索和个性化治疗建议.

结论:

  • 整合KG对于推进TCM诊断和干预至关重要.
  • 创新技术有效地解决了NER和关系提取挑战.
  • 开发的TCM KG弥合了知识差距,并作为TCM研究和实践的宝贵资源.