知识标签网络生成机制研究

The Generation Mechanism of Label Network

在知识生成社区中,现实中的网络关系由于具有一些人为实际演化特征,而与传统经典模型并不相符。该文将网络的批量增长和交叉连接特征引入到知乎社区标签网络中,对于网络演化过程进行动态分析,提出了一种标签网络优先连接模型,用来模拟知识标签网络中参数时间序列的复杂性。结果发现,该模型的仿真效果与实际情况下的知识标签网络吻合良好,且用时变方法分析网络的动态趋势较静态分析方法更为合理,该模型有助于后期深入了解现实世界中的复杂网络。

In the knowledge generation community,the network relationship in the real world does not match the traditional classic model because of some artificial evolution characteristics.In this paper,the parameter distribution and time-varying characteristics of the network are introduced into the network,and the evolution process of the network is analyzed dynamically,which provides an objective reference for the construction of the network.Based on the quantitative analysis of label network parameters,this paper proposes a knowledge label connection model based on Barbesi-Albert(BA)model,named batch cross-linking BA model,to simulate the complexity of the time-varying parameter series in generation process of the knowledge label network.The simulation results of the model are in good agreement with the actual knowledge label network.This model is helpful for us to understand the complex network in the real world.At the same time,it is more reasonable to use time-varying analysis method to analyze the dynamic trend of the network than static analysis method.