基于知识图谱分析的产业创新评估预测模型研究

A Novel Industrial Innovation Evaluation and Prediction Model Based on Knowledge Graph Analysis

[目的]知识图谱分析的自动化程度与动态性能不高,一直是其运用于产业创新研究领域的主要障碍。[方法]为解决上述难题,提出了基于知识图谱分析的产业创新预测模型;给出了该模型的框架结构、功能模块以及运作流程,详述了其中的关键算法;该模型通过灰色分图算法对产业创新项目规划进行内容界定与可能性评估,通过知识图谱生长衍化算法对产业创新未来趋势进行预测。[结果]实测结果表明,该模型比既有的预测模型,具有更高的分图收敛速度和图谱覆盖度,并具备较为精准的预测能力。

[Objective] The low automation and dynamic processing capability of knowledge graph analysis systems and models are major obstacles in the advance of industrial innovation evaluation and prediction applications. [Context] In order to deal them,a novel industrial innovation evaluation and prediction model was proposed based on knowledge graph analysis. And its frameworks,functional modules,and working flows were given as following. By a novel grey sub graph algorithm,the model made industrial innovation project planes content definition and possibility assessment. And a knowledge graph growth and evolution algorithm was used to predict the future trend of industrial innovation. [Results] Actual measurement results showed that the model had better sub-graph convergence rate,graph coverage,and prediction efficiency than the traditional does.