Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Synaptic Signaling01:09

Synaptic Signaling

5.5K
Neurons communicate at synapses, or junctions, to excite or inhibit the activity of other neurons or target cells, such as muscles. Synapses may be chemical or electrical.
Most synapses are chemical, meaning an electrical impulse or action potential spurs the release of chemical messengers called neurotransmitters. The neuron sending the signal is called the presynaptic neuron, and the neuron receiving the signal is the postsynaptic neuron.
The presynaptic neuron fires an action potential that...
5.5K
Integration of Synaptic Events01:28

Integration of Synaptic Events

1.5K
Synaptic integration mainly includes the summation of graded potentials. Graded potentials, regardless of their type, cause subtle alterations in membrane voltage, resulting in either depolarization or hyperpolarization. These incremental changes, when combined or summed, can propel the neuron toward its threshold. Consider, for example, a membrane experiencing a +15 mV shift, causing it to depolarize from -70 mV to -55 mV. In this scenario, graded potentials govern the membrane's ability to...
1.5K
The Anchoring-and-Adjustment Heuristic01:25

The Anchoring-and-Adjustment Heuristic

7.2K
In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. However, sometimes, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the...
7.2K
Schemas01:42

Schemas

11.6K
A schema is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). There are many different types of schemata, and they all have one thing in common: schemata are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed.
11.6K
Affinity and Avidity01:41

Affinity and Avidity

36.0K
Overview
36.0K
The Availability Heuristic01:08

The Availability Heuristic

6.0K
A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):
6.0K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Injectable cartilage matrix hydrogel loaded with cartilage endplate stem cells engineered to release exosomes for non-invasive treatment of intervertebral disc degeneration.

Bioactive materials·2022
Same author

Purification of Low-Concentration Carbonyl Sulfide by Red Mud-Based Adsorbent.

Bulletin of environmental contamination and toxicology·2022
Same author

[Transglutaminase 2 inhibits the proliferation of H1 subtype influenza virus in MDCK cells].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology·2022
Same author

Extrapulmonary lymphangioleiomyomatosis presenting as uterine round ligament lesion: A case report.

Asian journal of surgery·2022
Same author

A Positivity-Preserving Finite Volume Scheme for Nonequilibrium Radiation Diffusion Equations on Distorted Meshes.

Entropy (Basel, Switzerland)·2022
Same author

Altered Processing of Social Emotions in Individuals With Autistic Traits.

Frontiers in psychology·2022
Same journal

DARUMA: a gateway to fast and easy prediction of intrinsically disordered regions.

PeerJ. Computer science·2026
Same journal

Alzheimer's disease detection using a quantum deep neural network with Haralick feature extraction and simulated annealing optimization.

PeerJ. Computer science·2026
Same journal

Network anomaly detection using Deep Autoencoder and parallel Artificial Bee Colony algorithm-trained neural network.

PeerJ. Computer science·2026
Same journal

An anomaly detection model for multivariate time series with anomaly perception.

PeerJ. Computer science·2026
Same journal

Retraction: A wormhole attack detection method for tactical wireless sensor networks.

PeerJ. Computer science·2026
Same journal

Evaluation of mental disorder with prioritization of its type by utilizing the bipolar complex fuzzy decision-making approach based on Schweizer-Sklar prioritized aggregation operators.

PeerJ. Computer science·2026
查看所有相关文章

相关实验视频

Updated: Jul 1, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

1.6K

一个知识图嵌入基于模型的注意力机制,用于增强节点信息集成.

Ying Liu1,2, Peng Wang1,3, Di Yang1

  • 1School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China.

PeerJ. Computer science
|March 4, 2024
PubMed
概括
此摘要是机器生成的。

本研究引入了一种新的知识嵌入模型,使用图表注意力来改善罕见实体的表示,并提高链接预测的准确性. 该方法显著提高了性能,特别是对于连接有限的节点.

关键词:
人工智能的人工智能是人工智能.图表注意力机制的机制.知识图嵌入知识图.链接预测链接预测

更多相关视频

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

3.8K
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

555

相关实验视频

Last Updated: Jul 1, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

1.6K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

3.8K
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

555

科学领域:

  • 人工智能的人工智能
  • 数据科学数据科学数据科学
  • 图形神经网络 图形神经网络

背景情况:

  • 知识嵌入摘录图形数据为下游任务的矢量.
  • 现有的方法与大型数据集,有限的计算能力和罕见的实体表示作斗争.

研究的目的:

  • 开发一种知识嵌入模型,解决当前方法的局限性.
  • 改进罕见实体的表示,并提高链接预测的准确性.

主要方法:

  • 整合了一个图表注意力机制,以整合关键节点信息和汇总全球图形结构.
  • 开发了一个关系更新层,以完善关系表示后实体培训.
  • 专注于独立于它们有限的结构信息来表示罕见节点.

主要成果:

  • 拟议的模型在FB15K-237数据集上的链接预测中实现了与基线模型相匹配或超越的性能.
  • 与排名第二的基线相比,Hits@1指标增加了10.9%.
  • 在嵌入较少连接的罕见节点方面表现出卓越的准确性.

结论:

  • 新的知识嵌入模型有效地解决了当前方法的局限性.
  • 图表注意力和关系更新机制增强了实体的表示,特别是罕见的实体.
  • 该模型显示了改善基于知识图的应用程序 (如链接预测) 的巨大潜力.