[目的/意义]研究时间因素对专利被引频次的影响,可以减少时间因素对技术评价活动的制约,提高评价的准确性和可信度。[方法/过程]采集1975-2017年的美国专利数据,开展基于固定效应法的专利被引频次的修正研究。将专利按照不同公开年份和不同技术领域分组,选定组内均值和6个TOP分位数为被引频次基准,统计当前时间点的被引频次基准线及基准线的历史时序变化情况。建立神经网络模型,拟合基准线的时序变化规律,并预测未来统计时间点的基准线。[结果/结论]专利公开年份和统计年份的时间差异,使得专利被引频次无法直接进行比较。本文建立了基于不同技术领域、不同公开年份和不同统计年份的专利被引频次基准线,为专利评估提供参考。
[Purpose/significance] To study the influence of time factor on patent cited frequency can reduce the restriction of time factor on technical evaluation activities and improve the accuracy and reliability of evaluation.[Method/process] This paper collected U.S. patent data from 1975 to 2017, and carried out the revision study of patent cited frequency based on fixed effect method. The patents were grouped according to different publication years and different technical fields. Group mean and six TOP quantiles were selected as the benchmarks of patent cited frequency, and the benchmarks of patent cited frequency for both the current time point and the historical time series were counted. Then a neural network model was established to fit the timing variation of the benchmarks, thus predicting the benchmarks of future statistical time points.[Result/conclusion] The time difference between publication years and statistical years of patents makes it impossible to directly compare patent citations. This paper establishes benchmarks for patent citations based on different technical fields, different publication years and different statistical years, providing reference for patent evaluation.
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