本文构建科技主体间专利技术交易网络,从网络内生结构、科技主体间关系属性、科技主体个体属性等多维度提出影响专利交易的假设变量,建立复杂网络指数随机图模型(ERGM),预测科技主体间专利技术交易机会.通过2012-2016年新能源领域专利技术的实证研究,并将ERGM预测精度与传统链接预测方法对比,验证了ERGM在预测方面的优势和可行性.该研究一方面为技术交易网络中主体间交易机会预测提供有效方法,另一方面为专利技术交易推荐与主体对接提供决策.%To improve the efficiency of patent technology transfer and solve the problem of insufficient application of the effective supply of scientific and technological innovation,we construct the patent transaction network among the body of technology,propose the hypothesis variables of effecting patent transaction considering the multi-dimensional properties e.g. the endogenous structure of network, the relationship properties between body of technology and the individual attributes,then a complex network model is established based on exponential random graph model(ERGM)to predict opportunities of patent technology transactions and recommend the patent technology for supply and demand body. The advantages and feasibility of ERGM are verified in prediction by empirical study of patent technology in the new energy field in 2012-2016 and comparison the prediction accuracy of ERGM with the traditional method of link prediction. This study provides an effective method for the opportunities prediction of technology transaction between the body in technology transaction network and decision support for the patent recommendation of supply and demand and partners matching.
展开▼
