基于专利计量的技术融合研究:判定、现状与趋势——以物联网与人工智能领域为例
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摘要
选择物联网与人工智能领域为对象,基于专利数据,利用融合的专利申请量、技术距离和技术融合度来判断技术融合的情况;利用CiteSpace构建德温特手工代码共现矩阵,绘制共现图谱呈现融合后的知识结构、规律和分布情况;运用文献计量4个指标,探索技术融合后的技术研究现状和未来发展动向,为技术融合的相关研究拓宽思路。结果显示,2个领域间的技术融合在不断加强,图像、语音识别等相关技术是当前的热点技术,语音分析等相关技术可能成为未来的发展趋势。
The article selects the field of internet of things and artificial intelligence as the object, based on the patent data, using the amount of patent application, technical distance and technology fusion degree to judge the situation of technology fusion. We used CiteSpace to construct the Derwent manual code co-occurrence matrix, draw the co-occurrence map and presenting the knowledge structure, laws and distribution of after fusion,used the four indicators of bibliometric to explore the research status and future development trends after technology fusion,and broadened the thinking for the related research of technology fusion. The results show that the technology fusion between the two fields is constantly strengthening. Related technologies such as image and speech recognition are current hotspot technologies, and related technologies such as speech analysis may become the future development trend.
The article selects the field of internet of things and artificial intelligence as the object, based on the patent data, using the amount of patent application, technical distance and technology fusion degree to judge the situation of technology fusion. We used CiteSpace to construct the Derwent manual code co-occurrence matrix, draw the co-occurrence map and presenting the knowledge structure, laws and distribution of after fusion,used the four indicators of bibliometric to explore the research status and future development trends after technology fusion,and broadened the thinking for the related research of technology fusion. The results show that the technology fusion between the two fields is constantly strengthening. Related technologies such as image and speech recognition are current hotspot technologies, and related technologies such as speech analysis may become the future development trend.
引文
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韩震,沈君,曲莎莎. 2013. RFID技术趋势及竞争态势的专利计量分析[J]. 科研管理,34(7):11-16.
侯剑华,都佳妮. 2015. 基于专利计量与信息可视化的技术热点检测分析[J]. 现代情报,35(2):67-86.
栾春娟. 2012.“纳米—生物”会聚技术的测度及启示[J]. 科研管理,33(7):48-58.
邱均平,杨强. 2014. 技术融合计量分析:以4种新兴信息技术为例[J]. 图书情报工作,58(14):90-97.
黄鲁成,黄斌,吴菲菲,等. 2014. 基于专利共类的信息与生物技术融合趋势分析[J]. 情报杂志,33(8):59-63.
李姝影,方曙. 2017. 测度技术融合与趋势的数据分析方法研究进展[J]. 数据分析与知识发现,1(7):2-12.
王贤文,刘则渊,侯海燕.2010.基于专利共被引的企业技术发展与技术竞争分析:以世界500强中的工业企业为例[J].科研管理,31(4):127-138.
陈亮,张志强,尚玮姣.2013.技术融合研究进展分析[J].情报杂志,32(10):99-105.
陈悦,陈超美,刘则渊,等.2015.CiteSpace知识图谱的方法论功能[J].科学学研究,33(2):242-253.
李杰,陈超美.2017.CiteSpace:科技文本挖掘及可视化[M].北京:首都经济贸易大学出版社.
张振刚,黄洁明,陈一华.2018.基于专利计量的人工智能技术前沿识别及趋势分析[J].科技管理管理研究,38(5):36-42.
刘志迎,单洁含.2013.技术距离、地理距离与大学-企业协同创新效应:基于联合专利数据的研究[J].科学学研究,31(9):1331-1337.
Caviggioli F.2016.Technology fusion:Identification and analysis of the drivers of technology convergence using patent data[J].Technovation,(55/56):22-23.
Curran C S,Broring S,Leker J.2010.Anticipating converging industries using publicly available data[J].Technological Forecasting&Social Change,77(3):385-395.
Curran C S,Leker J.2001.Patent indicators for monitoring convergence-examples from NFF and ICT[J].Technological Forecasting&Social Change,78(2):256-273.
Chen C,Hu Z,Liu S,et al.2012.Emerging trends in regenerative medicine:Ascientometric analysis inCiteSpace[J].Expert Opinion on Biological Therapy,12(5):593-608.
Chen C,Ibekwe-Sanjuan F,Hou J.2010.The structure and dynamics of cocitation clusters:A multiple-perspective cocitation analysis[J].Journal of the American Society for Information Science and Technology,61(7):1386-1409.
Freeman L C.1977.A set of measures of centrality based on betweenness[J].Sociometry,40(1):35-41.
Griliches Z.1990.Patent statistics as economic indicators:A survey[J].Journal of Economic Literature,28(4):1661-1707.
Gubbi J,Buyya R,Marusic S,et al.2013.Internet of things(IOT):A vision,architectural elements,and future directions[J].Future Generation Computer Systems,29(7):1645-1660.
Jaffe A.1986.Technological opportunity and spillovers of R&D:Evidence from firms'patents,profits and market value[J].American Economic Review,76(5):984-1001.
Kleinberg J.2003.Bursty and hierarchical structure in streams[J].Data Mining and Knowledge Discovery,7(4):373-397.
Rosenberg N.1963.Technological change in the machine tool industry[J].Journal of Economic History,23(4):414-443.
Trajtenberg M,Henderson R,Jaffe A.1997.University versus corporate patents:A window on the basicness of invention[J].Economics of Innovation and New Technology,5(1):19-50.
Trappey A J C,Trappey C V,Hareesh Govindarajan U,et al.2017.A review of essential standards and patent landscapes for the internet of things:A key enabler for Industry 4.0[J].Advanced Engineering Informatics,(33):208-229.