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相关概念视频

Constraints and Statical Determinacy01:26

Constraints and Statical Determinacy

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In structural engineering, the equilibrium of a system is not only determined by its equations of equilibrium but also with the help of constraints. Constraints refer to restrictions on the motion of a system. The proper combinations of constraints can minimize the total number of constraints needed to maintain a system in mechanical equilibrium. When this happens, the system is said to be statically determinate. For such systems, the unknown reaction supports can be estimated using equilibrium...
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Structural Classification of Joints01:20

Structural Classification of Joints

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Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
A fibrous joint is where the adjacent bones are united by fibrous connective...
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Deductive Reasoning01:16

Deductive Reasoning

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Deductive reasoning, or deduction, is the type of logic used in hypothesis-based science. In deductive reasoning, the pattern of thinking moves in the opposite direction as compared to inductive reasoning, which means that it uses a general principle or law to predict specific results. From those general principles, a scientist can deduce and predict the specific results that would be valid as long as the general principles are valid.
For example, a researcher can deduce specific predictions...
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Functional Classification of Joints01:09

Functional Classification of Joints

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Functional Classification of Joints
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses  or amphiarthroses, whereas all synovial joints are classified as diarthroses.
Synarthrosis
An...
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Relationship Formation02:12

Relationship Formation

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What do you think is the single most influential factor in determining with whom you become friends and whom you form romantic relationships? You might be surprised to learn that the answer is simple: the people with whom you have the most contact. This most important factor is proximity. You are more likely to be friends with people you have regular contact with. For example, there are decades of research that shows that you are more likely to become friends with people who live in your dorm,...
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Types of Records II: Educational and Administrative Records01:18

Types of Records II: Educational and Administrative Records

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Maintaining nurses' educational and administrative records in healthcare settings, including hospitals and nursing schools, is paramount. Here's a breakdown of the types of academic records mentioned:
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相关实验视频

Updated: Jan 8, 2026

Executing Complexity-Increasing Queries in Relational MySQL and NoSQL MongoDB and EXist Size-Growing ISO/EN 13606 Standardized EHR Databases
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文件级关系提取与实体类型约束.

Ridong Han1, Tao Peng2, Beibei Zhu3

  • 1School of Computer Science and Technology/School of Artificial Intelligence, China University of Mining and Technology, Xuzhou, 221116, Jiangsu, China; College of Computer Science and Technology, Jilin University, Changchun, 130012, Jilin, China; Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, 130012, Jilin, China.

Neural networks : the official journal of the International Neural Network Society
|December 17, 2025
PubMed
概括
此摘要是机器生成的。

本研究引入了一种新的方法,通过使用实体类型约束来学习关系相关性来改进文档级关系提取. 这种方法有效地解决了长尾问题和关系提取任务中的多标签分类等挑战.

关键词:
在文档级别的文档级别.实体类型约束 实体类型约束关系提取 关系提取类型受约束的图形.类型受约束的损失.

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Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
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科学领域:

  • 自然语言处理自然语言处理.
  • 人工智能的人工智能

背景情况:

  • 文档级别的关系提取面临着长尾和多标签问题的挑战.
  • 使用变压器或文档图形的现有方法很难有效地解决这些问题.

研究的目的:

  • 提出一种使用实体类型约束来学习关系相关性的新方法,以改善文档级关系提取.
  • 解决当前处理长尾和多标签关系提取场景的方法的局限性.

主要方法:

  • 从全球和地方的角度来看,学习关系的相关性.
  • 构建实体类型和关系之间的类型受约束图,以实现全球相关性.
  • 提出一种类型受约束的损失,以提高本地匹配关系的分类概率.

主要成果:

  • 拟议的模型显著优于DocRED和DWIE数据集的现有基线.
  • 在处理长尾和多标签关系提取设置方面证明有效.
  • 实体类型约束成功指导学习关系相关性.

结论:

  • 通过实体类型约束来学习关系相关性是文档级关系提取的一个有希望的方向.
  • 拟议的方法为应对长尾和多标签挑战提供了强大的解决方案.
  • 这项工作推进了从文件中提取信息的最新技术.