基于概念格的企业群体创新偏好挖掘研究

Research on Mining Enterprise Group Innovation Preference Based on Concept Lattice

摘要:

在中国多项核心技术面临“卡脖子”问题的宏观背景下，充分挖掘发现不同企业群体的创新偏好全貌信息有助于进一步提升企业创新资源配置效能，最大化撬动企业创新能力和政府投资效率。为了精准捕捉各类企业创新偏好信息，本文提出一种专利数据驱动下基于模糊三支概念格对企业创新偏好进行群体画像的模型，以专利IPC信息为切入点层次化抽取企业群体创新偏好共性特征，实现领导型、稳定型、潜力型、危险型四类企业创新偏好的差异化多粒度刻画。在此基础上提出模糊三支概念格相似度定义，构建带有相似度的创新偏模糊三支概念格，揭示各企业间创新偏好关联关系。以中国集成电路设计行业数据为例进行实证验证模型有效性，结果表明模型可以清晰展现各类企业差异化创新偏好领域布局以及结构布局，为企业竞争战略制定及政府创新决策提供理论依据及参考。

Abstract:

Under the macro background that many core technologies in China are facing the "neck sticking" problem, fully mining and discovering the comprehensive information of innovation preferences of different enterprise groups will help to further improve the efficiency of enterprise innovation resource allocation, and maximize the innovation ability of enterprises and the efficiency of government investment. In order to accurately capture various types of enterprise innovation preference information, this paper proposes a patent data-driven group portrait model based on Fuzzy three branch concept lattice for enterprise innovation preference. Taking patent IPC information as the breakthrough point, it achieves the goal of leadership, stability, potential and innovation The differentiation and multi granularity characterization of innovation preferences of four types of dangerous enterprises. On this basis, the innovation partial fuzzy three branch concept lattice with similarity is constructed to reveal the relationship of innovation preference among enterprises. Taking the data of China's IC design industry as an example to verify the effectiveness of the model, the results show that the model can clearly show the field layout and structural layout of various types of enterprises' differentiated innovation preference, and provide theoretical basis and reference for enterprises' competitive strategy formulation and government innovation decision-making.