支持规避设计的海量专利质量评价模型
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摘要
专利规避设计需从现有专利中遴选具有核心竞争力的目标专利,以提升技术起点。针对设计领域的海量专利信息,提出了专利质量多指标主客观综合评价模型。分析专利书目信息与专利质量存在的正相关关系,甄选存活期、权利项数、同族专利数、引证数和被引证数等书目信息指标,构建了专利质量多指标综合评价指标体系,提升了评价方法的科学性和可操作性;提出将德尔菲法、层次分析法和均方差决策法相结合的主客观赋权法,确定专利质量评价指标权重,既保证了评价的权威性,又减小了个人偏见与从众妥协等因素的影响;建立了基于质量评价模型遴选目标专利的过程模型,并通过应用实例验证了该模型对遴选具有核心竞争力专利的有效性。
Sifting a target patent with core competitiveness through existing patents is the key step of patent circumvention to raise the starting point. For massive patents in design domain, a multi-index evaluation model was proposed, which effectively integrates subjective and objective weights. To improve the scientificalness and operability of evaluation indicators, the positive correlations between patent bibliographic data and patent quality were analyzed. As a result, five bibliographical data, i.e. patent duration, claims number, family number, citing number and cited number, were selected as indexes to establish a comprehensive evaluation system of patent quality. By combining Delphi Method, Analytic Hierarchy Process and Mean Square Error Decision Method, the objective and subjective weighting approach was presented to ensure authority of the evaluation result and reduce effects of personal bias and compromises. A process model of selecting target patents based on the patent quality evaluation model was built and applied in a real case of patent circumvention. The results show that the model improves the overall efficiency of finding target patents with core competitiveness.
Sifting a target patent with core competitiveness through existing patents is the key step of patent circumvention to raise the starting point. For massive patents in design domain, a multi-index evaluation model was proposed, which effectively integrates subjective and objective weights. To improve the scientificalness and operability of evaluation indicators, the positive correlations between patent bibliographic data and patent quality were analyzed. As a result, five bibliographical data, i.e. patent duration, claims number, family number, citing number and cited number, were selected as indexes to establish a comprehensive evaluation system of patent quality. By combining Delphi Method, Analytic Hierarchy Process and Mean Square Error Decision Method, the objective and subjective weighting approach was presented to ensure authority of the evaluation result and reduce effects of personal bias and compromises. A process model of selecting target patents based on the patent quality evaluation model was built and applied in a real case of patent circumvention. The results show that the model improves the overall efficiency of finding target patents with core competitiveness.
引文
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[2]DE RASSENFOSSE G,JAFFE A B.Are patent fees effective at weeding out low‐quality patents?[J].Journal of Economics&Management Strategy,2017,27(1):1-22.
[3]GRIMALDI M,CRICELLI L,GIOVANNI M D,et al.The patent portfolio value analysis:a new framework to leverage patent information for strategic technology planning[J].Technological Forecasting&Social Change,2015,94(1):286-302.
[4]VAN TRIEST S,VIS W.Valuing patents on cost-reducing technology:A case study[J].International Journal of Production Economics,2007,105(1):282-292.
[5]江屏,王川,孙建广,等.IPC聚类分析与TRIZ相结合的专利群专利规避方法与应用[J].机械工程学报,2015,51(7):144-154.JIANG Ping,WANG Chuan,SUN Jianguang,et al.Method and application of patent design around by combination of IPCcluster analysis and TRIZ[J].Journal of Mechanical Engineering,2015,51(7):144-154.
[6]穆秀秀,曹国忠,魏丛格,等.核心专利群专利规避案例研究[J].工程设计学报,2015,51(3):201-210.MU Xiuxiu,CAO Guozhong,WEI Congge,et al.Case studies of design around the group of core patents[J].Chinese Journal of Engineering Design,2015,51(3):201-210.
[7]LI M,MING X G,ZHENG M K,et al.A framework of product innovative design process based on TRIZ and patent circumvention[J].Journal of Engineering Design,2013,24(12):830-848.
[8]KAPOOR R.Patent value indicators as proxy for commercial value of inventions[J].International Journal of Intellectual Property Management,2013,6(3):217-232.
[9]DECHEZLEPRETRE A,MENIERE Y,MOHNEN M.International patent families:from application strategies to statistical indicators[J].Scientometrics,2017,111(2):793-828.
[10]LIU Y,HSEUH P,LAWRENCE R,et al.Latent graphical models for quantifying and predicting patent quality[C].Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining.ACM,2011:1145-1153.
[11]FISCKER T,LEIDINGER J.Testing patent value indicators on directly observed patent value-an empirical analysis of Ocean Tomo patent auctions[J].Research Policy,2014,43(3):519-529.
[12]FRIETSCH R,NEUHAUSLER P,JUNG T,et al.Patent indicators for macroeconomic growth-the value of patents estimated by export volume[J].Technovation,2014,34(9):546-558.
[13]邹正.固体非能源矿产资源地下开采回采率等级评价探讨[D].南宁:广西大学,2014.ZOU Zheng.Discussion of level evaluation of solid non-energy underground mining recovery rate[D].Nanning:Guangxi University,2014.
[14]LAND K C,SCHNEIDER S H.Forecasting in the social and natural sciences[M].Dordrecht:D.Reidel Publishing Company,
[15]MORRIS C,HOOGENES J,SHAYEGAN B,et al.Towards development and validation of an intraoperative assessment tool for robot-assisted radical prostatectomy training:results of a Delphi study[J].International Brazilian Journal of Urology,2017,43(4):661-670.
[16]赵又群,刘英杰.基于改进模糊层次分析法的汽车操纵稳定性主观综合评价[J].中国机械工程,2013,24(18):2519-2523.ZHAO Youqun,LIU Yingjie.Research on subjective evaluation indexes for vehicle handing stability based on improved analytic hierarchy process and fuzzy comprehensive evaluation[J].China Mechanical Engineering,2013,24(18):2519-2523.
[17]王明涛.多指标综合评价中权数确定的离差、均方差决策方法[J].中国软科学,1999(8):100-101.