政策血缘关系网络构建与传播演化机理研究

政策体系是一个庞大的系统,R政策碎片化日益严重导致政策不一致性。本文通过挖掘政策血缘关系对政策系统进行建模,将数量庞大的政策形式化为政策血缘网络。在此基础上构建PCL模型,通过机器学习确定模型中节点的容量定义,实现政策网络中脆性点挖掘。该方法通过挖掘政策间的相关概念,将政策体系形式化为政策谱系树模型,再由政策谱系树的节点对之间发生“树影相吸”,最终形成基于政策血缘关系的政策血缘网络。通过政策血缘网络的传播演化机理,构建了PCRL模型,通过机器学习对容量参数进行参数训练,挖掘传播演化机理。最后选取政策实例进行仿真实验,验证了方法的有效性。

Text lineage network construction and evolution mechanism of communication

In this paper, the lineage from a policy text perspective modeling approach. The method is an industry policy text formalized policies lineage tree. Between policy text lineage tree node "shadows attract", eventually forming policy based network text lineage relationship. And on the basis of the policy text on the basis of lineage network nodes in the network referral value, evaluate and dominant policy points found kinship network text, through the dissemination of policy text lineage network evolution mechanism constructed PCRL model, and the model based on PCL above, to achieve a brittle point of excavation and to mine the evolution mechanism. Finally, the policy text experiment in the field of modeling and analysis methods used in the field of policy text points specific area of policy research.