知识网络演化模型的仿真研究(英文)  

Simulation Research on Evolving Model of Knowledge Network

作　　者：单海燕[1] 王文平[2] 王娇俐[2] 

机构地区：[1]南京信息工程大学经济管理学院,南京210044 [2]东南大学经济管理学院,南京210096

出　　处：《系统仿真学报》2011年第1期80-84,共5页Journal of System Simulation

基　　金：supported by National Natural Science Foundation of P.R.China(70571013,70973017);New Century Excellent Talents Award(NCET-06-0471)

摘　　要：研究了一类基于知识相关度的局部偏好连接机制和偏好删除机制的知识网络演化模型。数值模拟了知识网络累积度分布,累积度分布一开始近似服从无标度分布,而后出现一指数截断。最后比较了在一些不同连接与删除机制下生成的一些知识指标,仿真结果表明,基于知识的局部偏好连接机制和基于度的偏好删除机制比随机局部偏好连接机制和随机偏好删除机制更易于引起网络异质性及提高网络的绩效,而这些指标是有利于网络的形成。A new type of knowledge network evolving model which comprises node addition and node deletion with the concept of local world preferential connection mechanism based on knowledge correlation degree and preferential deletion mechanism is studied. A series of numerical simulations of the cumulative degree distribution of the knowledge networks are conducted. The cumulative degree distribution at first has the property of scale-free approximately, and then it aLmS into an exponential truncation. Finally some knowledge indices generated by different connection and deletion mechanisms are compared. The results of simulations show that knowledge-based local world preferential connection mechanism and degree-based preferential deletion mechanism are prone to arousing heterogeneity and improving performance of the network comparing to the random local world preferential connection mechanism and random preferential deletion mechanism, which are advantageous to network formation.

关 键 词：无标度网络 知识网络 网络结构 知识相关度 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]