跨领域颠覆性技术主题识别研究——以脑科学技术为例

Research on Cross Domain Disruptive Technology Theme Identification:A Case Study of Brain Science

[目的/意义]颠覆性技术是引领当今世界经济发展的关键驱动力,跨领域颠覆性技术往往对技术的发展具有更加深刻的价值和意义,预先科学准确地识别跨领域颠覆性技术,是超前捕获技术发展方向并抢占科技竞争主动权的关键。[方法/过程]基于跨领域融合创新思想,构建跨领域颠覆性技术主题的识别方法和总体框架。具体采用ISI-OST-INPI分类体系与Rao-Stirling多样性指数,综合考虑专利所涉及技术领域的多样性、均匀度和差异性,对跨领域专利进行筛选后,运用文本挖掘和社会网络分析方法,构建跨领域专利关键词时序共现网络并聚类形成技术主题,并从网络内部知识流动的角度,结合跨领域颠覆性技术特征构建多维测度指标与综合得分,识别跨领域颠覆性技术主题。最后选取脑科学专利开展实证研究。[结果/结论]结果表明,类脑器官培育和神经干细胞的移植分化、脑机接口技术及应用、神经形态计算3个技术主题具有较强的跨领域颠覆性特征,并通过资料验证法进行结果验证,证明识别方法的可行性和有效性。

[Purpose/Significance]Disruptive technology is a key driving force that leads the development of the world economy today.Cross domain disruptive technology often has more profound value and significance for the development of technology.Accurately identifying cross domain disruptive technology in advance is the key to capturing the direction of technological development and seizing the initiative in scientific and technological competition.[Method/Process]Based on the idea of cross domain fusion innovation,this article constructed a method for identifying disruptive technology themes across domains.Firstly,it adopted the ISI-OST-INPI classification system and Rao-Stirling diversity index,comprehensively considered the diversity,uniformity,and differences of the technical fields involved in the patents,and screened cross domain patents.Secondly,using text mining and social network analysis methods,it constructed a cross domain patent keyword temporal co-occurrence network and clustered it to form technical themes.Furthermore,it constructed multidimensional measurement indicators and comprehensive scores from the perspective of knowledge flow within the network,combined with the characteristics of cross domain disruptive technologies,to identify cross domain disruptive technology themes.Finally,it selected brain science patents for empirical research.[Result/Conclusion]The results indicate that the cultivation of brain-like organs and the transplantation of neural stem cells,brain computer interface technology and applications,and neural morphology computing have strong cross domain disruptive characteristics.The feasibility and effectiveness of the method have been verified through data validation.