arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv physics/0508132physics.soc-ph
收藏

通过专利引用系统的动力学描述来建模创新

Modeling innovation by a kinetic description of the patent citation system

Gabor Csardi, Katherine J Strandburg, Laszlo Zalanyi, Jan Tobochnik, Peter Erdi

摘要:

本文报告了美国专利制度研究的网络理论方法的结果。我们将专利引用网络建模为一个离散时间、离散空间的随机动态系统。从超过200万项专利及其引用的数据中,我们提取了一个吸引力函数$A(k,l)$,它决定了专利被引用的可能性。$A(k,l)$可近似地分为函数$A_k(k)$和函数$A_l(l)$的乘积,其中$k$是已经收到的引用数(以度为单位),$l$是以专利号为单位测量的年龄。$A_l(l)$在低$l$时显示出峰值和长幂律尾部,表明某些专利技术具有非常长期的影响。$A_k(k)$表现出超线性优先连接。自1991年以来,优先附着指数一直在上升,这表明专利引用越来越集中在相对较少的专利上。同一时期,一项新专利被某一专利引用的总体平均概率略有增加。我们讨论了我们的研究结果对专利政策的一些可能的影响。

英文摘要:

This paper reports results of a network theory approach to the study of the United States patent system. We model the patent citation network as a discrete time, discrete space stochastic dynamic system. From data on more than 2 million patents and their citations, we extract an attractiveness function, $A(k,l)$, which determines the likelihood that a patent will be cited. $A(k,l)$ is approximately separable into a product of a function $A_k(k)$ and a function $A_l(l)$, where $k$ is the number of citations already received (in-degree) and $l$ is the age measured in patent number units. $A_l(l)$ displays a peak at low $l$ and a long power law tail, suggesting that some patented technologies have very long-term effects. $A_k(k)$ exhibits super-linear preferential attachment. The preferential attachment exponent has been increasing since 1991, suggesting that patent citations are increasingly concentrated on a relatively small number of patents. The overall average probability that a new patent will be cited by a given patent has increased slightly during the same period. We discuss some possible implications of our results for patent policy.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑