基于单层引文网络的技术演进路径研究——以机器学习领域为例
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摘要
科学地把握技术发展动态和了解技术发展脉络对企业和政府制定创新战略具有重要意义。本文提出了一种基于专利单层引文网络社区划分识别技术演进路径的方法,并以机器学习领域为例,构建五个时间段下的专利单层引文网络,通过分析网络结构,发现机器学习领域存在一定的技术壁垒;接着使用社区发现算法识别专利主题,利用德温特手工代码映射主题内容,依据相邻时间段引文网络社区之间的引用强度构建主题演化冲积图,最终识别出四条主要技术演进路径,验证了方法的有效性,表明本文提出的方法有望对现有技术演进路径的分析方法起到一定的补充作用。
It is of great significance for enterprises and governments to scientifically grasp the development trend of the technology. A method is proposed in this paper to track technological evolution paths by community detection in original direct citation network. After constructing five successive citation networks in the patent field of Machine Learning, the key topics in every period are identified through community detection algorithm and the topic content are represented by Derwent Manual Code. Then it is found that there are certain technical barriers in the field of machine learning through the analysis of network structure. Finally, four main technological evolution paths are tracked by detecting strong connections between communities in adjacent sliced time periods, which show that the method proposed in this paper is expected to supplement the existing approaches of tracking technological evolution paths.
It is of great significance for enterprises and governments to scientifically grasp the development trend of the technology. A method is proposed in this paper to track technological evolution paths by community detection in original direct citation network. After constructing five successive citation networks in the patent field of Machine Learning, the key topics in every period are identified through community detection algorithm and the topic content are represented by Derwent Manual Code. Then it is found that there are certain technical barriers in the field of machine learning through the analysis of network structure. Finally, four main technological evolution paths are tracked by detecting strong connections between communities in adjacent sliced time periods, which show that the method proposed in this paper is expected to supplement the existing approaches of tracking technological evolution paths.
引文
[1]郭颖,朱东华,汪雪峰,等.科学技术可视化[J].科学学与科学技术管理,2011,32(12):36-44.
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[3]赵阳,文庭孝.专利技术信息挖掘研究进展[J].图书馆,2018(4):28-36.
[4]Suzuki J,Kodama F.Technological diversity of persistent innovators in Japan[J].Research Policy,2004,33(3):531-549.
[5]Wu C.Constructing a weighted keyword-based patent network approach to identify technological trends and evolution in a field of green energy:a case of biofuels[J].Quality&Quantity,2016,50(1):213-235.
[6]陈亮,张静,张海超,等.层次主题模型在技术演化分析上的应用研究[J].图书情报工作,2017(5):103-108.
[7]Wang B,Liu S,Ding K,et al.Identifying technological topics and institution-topic distribution probability for patent competitive intelligence analysis:a case study in LTE technology[J].Scientometrics,2014,101(1):685-704.
[8]李欣,谢前前,黄鲁成,等.基于SAO结构语义挖掘的新兴技术演化轨迹研究[J].科学学与科学技术管理,2018(1):17-31.
[9]王燕鹏.国内基于主题模型的科技文献主题发现及演化研究进展[J].图书情报工作,2016(3):130-137.
[10]陈亮,张志强.技术演化研究方法进展分析[J].图书情报工作,2012(17):59-66.
[11]许海云,王振蒙,胡正银,等.利用专利文本分析识别技术主题的关键技术研究综述[J].情报理论与实践,2016(11):131-137.
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[13]Verspagen B.Mapping technological trajectories as patent citation networks:A study on the history of fuel cell research[J].Advances in Complex Systems,2007,10(1):93-115.
[14]Martinelli A.An emerging paradigm or just another trajectory?Understanding the nature of technological changes using engineering heuristics in the telecommunications switching industry[J].Research Policy,2012,41(2):414-429.
[15]范维熙,费钟琳.基于德温特专利引文网络的技术演进路径研究--以太阳能电池技术为例[J].情报杂志,2014(11):62-66.
[16]杨中楷.混合动力汽车驱动系统技术轨道识别研究[J].情报工程,2016(2):8-17.
[17]黄鲁成,石媛嫄,吴菲菲.基于专利引用的技术轨道动态分析--以太阳能电池为例[J].科学学研究,2013,31(3):358-367.
[18]张娴,方曙.专利引用网络主路径方法研究述评与展望[J].图书情报工作,2016(20):140-148.
[19]Huang M,Chiang L,Chen D.Constructing a patent citation map using bibliographic coupling:A study of Taiwan’s high-tech companies[J].Scientometrics,2003,58(3):489-506.
[20]王健美,刘志芳,戴爱兵.纯电动汽车产业关键技术演进分析--专利引文分析视角[J].图书情报工作,2014(14):21-27.
[21]张文琪.综合主题分析的交叉学科合著网络演化研究[D].大连:大连理工大学,2016.
[22]罗双玲,张文琪,夏昊翔.基于半积累引文网络社区发现的学科领域主题演化分析--以“合作演化”领域为例[J].情报学报,2017(1):100-110.
[23]Blondel V D,Guillaume J,Lambiotte R,et al.Fast unfolding of communities in large networks[J].Journal of Statistical MechanicsTheory and Experiment,2008(10):155-168.
[24]Breitzman A F,Mogee M E.The many applications of patent analysis[J].Journal of Information Science,2002,28(3):187-205.
[25]Adner R,Levinthal D.Demand heterogeneity and technology evolution:Implications for product and process innovation[J].Management Science,2001,47(5):611-628.
[2]Dosi G.Sources,Procedures,and Microeconomic Effects of Innovation[J].Journal of Economic Literature,1988,26(3):1120-1171.
[3]赵阳,文庭孝.专利技术信息挖掘研究进展[J].图书馆,2018(4):28-36.
[4]Suzuki J,Kodama F.Technological diversity of persistent innovators in Japan[J].Research Policy,2004,33(3):531-549.
[5]Wu C.Constructing a weighted keyword-based patent network approach to identify technological trends and evolution in a field of green energy:a case of biofuels[J].Quality&Quantity,2016,50(1):213-235.
[6]陈亮,张静,张海超,等.层次主题模型在技术演化分析上的应用研究[J].图书情报工作,2017(5):103-108.
[7]Wang B,Liu S,Ding K,et al.Identifying technological topics and institution-topic distribution probability for patent competitive intelligence analysis:a case study in LTE technology[J].Scientometrics,2014,101(1):685-704.
[8]李欣,谢前前,黄鲁成,等.基于SAO结构语义挖掘的新兴技术演化轨迹研究[J].科学学与科学技术管理,2018(1):17-31.
[9]王燕鹏.国内基于主题模型的科技文献主题发现及演化研究进展[J].图书情报工作,2016(3):130-137.
[10]陈亮,张志强.技术演化研究方法进展分析[J].图书情报工作,2012(17):59-66.
[11]许海云,王振蒙,胡正银,等.利用专利文本分析识别技术主题的关键技术研究综述[J].情报理论与实践,2016(11):131-137.
[12]Hummon N P,Dorelan P.Connectivity in a citation network-The development of DNAtheory[J].Social Networks,1989,11(1):39-63.
[13]Verspagen B.Mapping technological trajectories as patent citation networks:A study on the history of fuel cell research[J].Advances in Complex Systems,2007,10(1):93-115.
[14]Martinelli A.An emerging paradigm or just another trajectory?Understanding the nature of technological changes using engineering heuristics in the telecommunications switching industry[J].Research Policy,2012,41(2):414-429.
[15]范维熙,费钟琳.基于德温特专利引文网络的技术演进路径研究--以太阳能电池技术为例[J].情报杂志,2014(11):62-66.
[16]杨中楷.混合动力汽车驱动系统技术轨道识别研究[J].情报工程,2016(2):8-17.
[17]黄鲁成,石媛嫄,吴菲菲.基于专利引用的技术轨道动态分析--以太阳能电池为例[J].科学学研究,2013,31(3):358-367.
[18]张娴,方曙.专利引用网络主路径方法研究述评与展望[J].图书情报工作,2016(20):140-148.
[19]Huang M,Chiang L,Chen D.Constructing a patent citation map using bibliographic coupling:A study of Taiwan’s high-tech companies[J].Scientometrics,2003,58(3):489-506.
[20]王健美,刘志芳,戴爱兵.纯电动汽车产业关键技术演进分析--专利引文分析视角[J].图书情报工作,2014(14):21-27.
[21]张文琪.综合主题分析的交叉学科合著网络演化研究[D].大连:大连理工大学,2016.
[22]罗双玲,张文琪,夏昊翔.基于半积累引文网络社区发现的学科领域主题演化分析--以“合作演化”领域为例[J].情报学报,2017(1):100-110.
[23]Blondel V D,Guillaume J,Lambiotte R,et al.Fast unfolding of communities in large networks[J].Journal of Statistical MechanicsTheory and Experiment,2008(10):155-168.
[24]Breitzman A F,Mogee M E.The many applications of patent analysis[J].Journal of Information Science,2002,28(3):187-205.
[25]Adner R,Levinthal D.Demand heterogeneity and technology evolution:Implications for product and process innovation[J].Management Science,2001,47(5):611-628.