Policy Text Relevance Analysis Based on Entity Knowledge Network——Taking China's Entrepreneurship Policies as an Example
The achievement of national political or economic goals often requires the coordinated implementation of all kinds of policies.Therefore,exploring the relationship and relevance among different policies is conducive to the scientific formulation and effective practice of such policies.However,current researches have done little in revealing the semantic level of policy text relevance.In order to know more about the relationship and relevance among different policies and discover the core policy in each policy group,this paper proposes a multi-level relevance mining framework of policy entity knowledge network.First,named entity recognition technologies are used to extract fine-grained policy knowledge objects in policy texts.Then,a multi-level policy entity knowledge network is constructed,and a quantitative calculation method based on Jaccard distance is designed.Afterwards,an analysis is conducted of the self-constructed a multi-level entrepreneurial policy entity knowledge network.The result shows that such a network can effectively reveal the potential relevance among different policy texts,discover the core policy in each policy group,and interpret the relationship among the policy texts from multiple dimensions.
policy relevance analysispolicy text calculationknowledge networkknowledge extraction
NETL
NSTL
万方数据
