项目名称: 基于被引科学知识突变的突破性创新动态识别及其形成机理研究
项目编号: No.71503125
项目类型: 青年科学基金项目
立项/批准年度: 2016
项目学科: 管理科学
项目作者: 张金柱
作者单位: 南京理工大学
项目金额: 17万元
中文摘要: 突破性创新动态识别及其预警和预测对规划技术发展方向、规避潜在落后技术、优化研发布局等具有重要意义,是亟需解决的现实问题;科学知识突变为引导技术突破发挥了基础性作用,而科学知识突变从哪些方面诱发、如何诱发突破性创新发生还需深入研究。因此,本项目以专利引用科学论文为纽带,以专利科学引文特征项及其关系表示被引科学知识,通过对其突变进行实时跟踪研究突破性创新的动态识别;分析导致突变发生的原因得到形成机理,对突破性创新进行预警和预测。首先构建被引科学知识的异构网络,对关系进行表示、抽取和关联强度计算,形成被引科学知识的关联模型;接着实时跟踪被引科学知识的异构网络结构演变和突变,形成基于模块度增量更新的突破性创新实时动态识别方法,设计突破性创新的突变程度归一化计算指标和方法;最后,跟踪被引科学知识发生突变的原因,分析突变程度高的专利,探讨和明晰突破性创新的形成机理以及科学知识对技术创新的影响机制。
中文关键词: 突破性创新;被引科学知识突变;动态识别;形成机理;专利科学引文
英文摘要: The dynamic detection and forecasting of radical innovation (RI) is significant for planning of technology development direction, avoiding potential outdated technology and optimizing research and development layout, which is always a focus and practical problem. Scientific knowledge mutation is fundamental to lead technology breakthrough, but where and how to lead the generation of RI need to deeply research. Therefore, the project from the perspective of the patents citing papers, utilize the features and relations of scientific references of patents to establish the cited scientific knowledge (CSK), for real-time tracking S&T development trends and forming mechanism to forecast RI. Firstly, using heterogeneous network to integrate multiple features and relations of CSK and compute the relation intensity. Secondly, tracking the evolution and mutation of CSK which expressed by structure mutation of heterogeneous network, to form the dynamic detection method of RI based on incremental modularity updating and normalized indicators for mutation degree. Finally, tracking how the CSK leads to RI, to probe the formation mechanism of RI and the impact mechanism from fundamental research to innovation.
英文关键词: radical innovation;mutation of cited scientific knowledge;dynamic detection;forming mechanism;scientific references in patents