基于知识图谱的区域企业关联可视化及关系挖掘

Regional Enterprise Association Visualization and Relationship Mining Based on Knowledge Graph

现有区域企业关联分析结果呈现复杂的网络结构,难以理解,而且区域企业关联在时间和空间上具有动态性。针对当前区域企业分析中存在的结果解释问题,本文提出一种基于知识图谱的区域企业关联分析模型。采用属性图建模方法,运用多源异构数据进行知识抽取和存储,并结合Neo4j图数据库实现区域企业关系的知识存储。在力导向布局方面,通过采用斥力优化求解和节点边处理,成功实现企业关系的可视化呈现。通过深入挖掘分析企业间的关联关系,旨在揭示区域企业之间的合作与竞争关系,为政府产业政策制定、企业招商引资和企业间合作提供决策支持。实验结果表明,该模型能够准确揭示企业间的关系,为区域经济发展提供有力支持。

Given the complex network structure of existing regional enterprise association analysis results,which is difficult to comprehend,and the dynamic nature of regional enterprise associations in time and space.In response to the challenges in inter⁃preting results in current regional enterprise analysis,this paper adopts a knowledge graph-based model for regional enterprise association analysis.It utilizes diverse and heterogeneous data for knowledge extraction and storage,coupled with the Neo4j graph database to realize knowledge storage of regional enterprise relationships.In terms of force-directed layout,the utilization of repulsive force optimization and node-edge processing successfully achieves the visualization of enterprise relationships.Through in-depth exploration and analysis of inter-enterprise associations,the aim is to reveal cooperation and competition rela⁃tionships among regional enterprises,providing decision support for government industrial policy formulation,enterprise invest⁃ment attraction,and inter-enterprise collaboration.Experimental results demonstrate that the model accurately reveals inter enterprise relationships,offering robust support for regional economic development.