摘要
【目的/意义】从大数据驱动角度出发,探索采用人工智能方法实现对政策文本协同性定量分析的可能性。【方法/过程】以政策全文本数据为研究对象,使用知识图谱技术实现不同主题的本体构建,并应用数据挖掘中关联规则构建推理模型,对图谱表示的政策文本进行协同性语义挖掘和推理。【结果/结论】围绕"开放数据"和"数据安全"主题构建知识图谱,实现对政策文本的本体表示,在此基础上使用关联规则完成单文本和多文本在两个主题间的协同性分析。【创新/局限】本文将知识图谱应用于政策文本分析领域,并完成协同性分析,为政策的全样本分析提供可能性,后续需扩大样本规模,提升推理效率。
【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/conclusion】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 analysis,which provides the possibility for the full sample analysis of policies.In the future the sample size should be expanded to improve reasoning efficiency.
作者
韩娜
马海群
刘兴丽
HAN Na;MA Hai-qun;LIU Xing-li(Information Resource Management Research Center of Heilongjiang University,Harbin 150080,china;School of computer and Information Engineering,Heilongjiang University of Science and Technology,Harbin 150020,China)
出处
《情报科学》
CSSCI
北大核心
2021年第11期180-186,共7页
Information Science
基金
国家社会科学基金重点项目“开放数据与数据安全的政策协同研究”(15ATQ008)
黑龙江大学对俄问题研究专项项目“俄罗斯信息安全体系研究”(DEZ1906)
黑龙江省高等教育教学改革项目“基于知识图谱学科热点的研究生创新能力培养的研究”(SJGY20190605)
关键词
政策文本协同
知识图谱
关联规则
定量分析
推理研究
policy text synergy
Knowledge Graph
association rules
quantitative analysis
reasoning research
