将高频信息纳入边缘卷积,用于复杂网络中的链路预测.
Zhiwei Zhang1, Haifeng Xu2, Guangliang Zhu2
1School of Informatics and Engineering, Suzhou University, Suzhou, 234000, China. zzwloveai@gmail.com.
Scientific reports
|March 5, 2024
概括
这项研究介绍了EdgeConvHiF,一种用于复杂网络中链接预测的新型图形神经网络. 通过集成高频节点信息,它克服了现有模型的局限性,提高了预测准确性和稳定性.
科学领域:
- 图形神经网络的神经网络
- 复杂的网络 复杂的网络
- 机器学习 机器学习
背景情况:
- 链接预测对于推系统,知识图表和生物医学研究至关重要.
- 当前的图形神经网络经常忽视高频节点信息,导致过度平滑和性能降低.
- 这限制了现有模型在准确预测链接方面的有效性.
研究的目的:
- 提出一个新的边缘卷积图神经网络,EdgeConvHiF,用于增强链接预测.
- 通过结合高频节点信息来解决图形神经网络中的过度平滑问题.
- 提高复杂网络中链接预测的准确性和稳定性.
主要方法:
- 开发了EdgeConvHiF,一个边缘卷积图神经网络模型.
- 将高频节点信息集成到表示学习过程中.
- 通过链接分类进行了链接预测.
主要成果:
- 在实验中,EdgeConvHiF表现出高稳定性.
- 拟议的模型在链接预测任务中表现优于现有的代表性基线.
- 通过对现实世界的网络基准进行广泛的实验来验证.
结论:
- EdgeConvHiF有效地将高频节点信息融合在一起,以实现卓越的链路预测.
- 该模型比目前的图形神经网络方法有显著的进步.
- EdgeConvHiF为复杂网络中的链接预测提供了稳定且有利的解决方案.
相关概念视频
Linear Approximation in Frequency Domain
89
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
89
End Point Prediction: Gran Plot
324
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
For potentiometric titration, the Gran plot is created by plotting...
324
Linear Approximation in Time Domain
81
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
81
Classification of Signals
460
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
460
Determination of Expected Frequency
2.2K
Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...
2.2K
Reducing Line Loss
152
In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss...
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss...
152


