面向科技大数据的颠覆性技术多维度识别算法

Multidimensional Recognition Algorithm for Disruptive Technology in Sci-tech Big Data

中文关键词: 颠覆性技术;科技评估;文献计量;CDt 指数;熵权法

英文关键词: disruptive technologies, science and technology assessment, bibliometrics, CDt index, entropy weight method

中文摘要:

      颠覆性技术具备“重塑”科技与市场未来格局的潜力。为支持科技评估中颠覆性技术的识别任务，提出一 种基于科技大数据的颠覆性技术自动化识别算法(MRA-DT)。首先，基于科技出版物引文网络结构、时序化特征、跨 领域影响和技术时效性等信息，设计了 4 个维度的颠覆性技术识别指标，并采用熵权法进行结果融合。然后，在计算 机科学和无线电通信领域进行实证研究。实证研究表明，MRA-DT 算法是一种可靠的工具，可以为科技情报分析人员 和相关管理者提供科技创新决策依据，对于企业抢占科技制高点、国家提升科技和国防实力具有重要意义。

英文摘要:

      Disruptive technologies have the potential to reshape the future landscape of both technology and markets. This paper aims to propose an automated algorithm for identifying disruptive technologies based on big data analysis, which can support the identification of disruptive technologies in technology assessment. The algorithm utilizes information such as the citation network structure of technology publications, temporal features, cross-disciplinary impact, and technological timeliness to design four dimensions of indicators for identifying disruptive technologies, and adopts the entropy weighting method for result fusion. Empirical research was conducted in the fields of computer science and wireless communication. The results demonstrate that the MRA-DT algorithm is a reliable tool that can provide decision-making support for technology intelligence analysts and related managers in technology innovation, which is of significant importance for companies to seize technological high ground, and for countries to enhance their technological and defense capabilities.