Generation of scale-free knowledge network with local world mechanism

局域世界机制下无标度知识网络的生成模型(英文)

In order to simulate the real growing process, a new type of knowledge network growth mechanism based on local world connectivity is constructed. By the mean-field method, theoretical prediction of the degree distribution of the knowledge network is given, which is verified by Matlab simulations. When the new added node＇s local world size is very small, the degree distribution of the knowledge network approximately has the property of scale-free. When the new added node＇s local world size is not very small, the degree distribution transforms from pure power-law to the power-law with an exponential tailing. And the scale-free index increases as the number of new added edges decreases and the tunable parameters increase. Finally, comparisons of some knowledge indices in knowledge networks generated by the local world mechanism and the global mechanism are given. In the long run, compared with the global mechanism, the local world mechanism leads the average knowledge levels to slower growth and brings homogenous phenomena.

为了更真实地模拟现实知识网络的成长过程,构造了一类基于局域连接机制下的知识网络生成模型.利用统计物理学中的平均场方法,给出了知识网络度分布的理论预测,并运用Matlab仿真进行了验证:当局域世界规模很小时,网络度的分布函数近似服从无标度分布,当局域世界规模不是很小时,网络度的分布会从纯粹的无标度状态变化成尾状物服从指数分布的近似无标度状态,且无标度指数随着可调参数增加而增加,随着新增边数的增加而减少.最后,比较了在局域连接机制和全局连接机制下生成的知识网络的一些知识指标.从长期来看,与全局机制相比,局域机制会导致网络平均知识水平增长缓慢,而且网络同质化现象严重.