基于二分网络多维投影的技术交易机会预测——以新能源领域专利技术为例

Technology Transaction Opportunity Prediction Based on Bipartite Network Multidimensional Projection——Exemplified by the Patent Technology in the Field of New Energy

构建专利技术与主体间的交易二分网络,考虑主体的交易技术偏好、主体间共同邻居的度以及主体与技术间的交易频次等对交易机会的影响,修正链接覆盖的模式权重,提出了基于二分网络多维投影的技术交易机会预测模型。通过新能源领域专利技术交易数据的实证研究,以及与传统的二分网络链路预测方法对比,得出:本文提出的方法相比传统方法,命中率显著提高,并通过随机选取10组数据集进行精度对比,验证了本文方法的准确性和稳健性;此外,实证研究表明:大企业集团内部的技术交易活跃,但对外辐射能力弱;高校和科研院所参与技术交易的程度不高;历史交易能够增强主体间信任关系和合作经验,对交易预测具有重要影响,主体交易的技术领域偏好和区域偏好也对预测精度提高具有一定贡献。本文提出的思路与方法不仅能够实现专利技术交易推荐,且能够通过技术推荐开展交易伙伴推荐,并预测未来交易的热点领域。

This paper constructs a transaction bipartite network between patent technology and subject.Considering the influence of technology preferences,degree of common neighbors and transaction frequency on transaction opportunities,this paper revises the pattern weight covered by links and proposes the technology transaction opportunities prediction model based on multidimensional projection of bipartite network.Through the empirical study of patent technology transaction data in the field of new energy and the comparison with the traditional bipartite network link prediction method,this paper concludes that the hit rate of the method proposed in this paper is significantly higher than that of the traditional method,and the accuracy and robustness of this method are verified by randomly selected 10 groups of data sets for comparison.In addition,the empirical study shows that the technology transaction within large enterprise groups is active but the external radiation is weak.Universities and scientific research institutes are less involved in transaction.The historical transaction can enhance the trust relationship and cooperation experience among the subjects,which has an important impact on the transaction prediction,and the technology and region preferences of subjects transaction also contribute to the improvement of prediction accuracy.The ideas and method proposed in this paper can not only realize the recommendation of patent technology transaction,but also carry out trading partner recommendation based on technology recommendation,and predict the hot areas of future transaction,which can provide decision support for promoting the development of technology market.