Abstract: 【Purpose/significance】Starting from the big data-driven perspective，the possibility of using artificial intelligence methods
to achieve a quantitative analysis of the synergy of policy texts is explored.【Method/process】The study takes the policy whole text data as the research object,uses the Knowledge Graph technology to realize ontology construction of different topics,and the association rules in data mining to construct a reasoning model,and perform synergy semantic mining and reasoning on the policy text.【Result/con? clusion】Based on the themes of "open data" and "data security",a knowledge graph is constructed to finish the ontology representation of the policy text.The synergy analysis between single text and multiple texts between the two topics is completed by the association rules.【Innovation/limitation】This paper applies the knowledge graph to the field of policy text analysis,and completes the synergy anal? ysis,which provides the possibility for the full sample analysis of policies.In the future the sample size should be expanded to improve reasoning efficiency.