Search path link count and search path node pair are applied to calculate the connectivity of citation path and a technological evolutionary trajectory extraction algorithm based on patent citation network is put forward. The 5,073 patents related to data mining which were granted during the period of 1975-1999 from database of United States Patent and Trademark Office are collected. The geographical distribution and annual distribution of the patents are analyzed. By querying the patent data set of NBER to get patent citation relations and the network analysis software of Pajek is used to build a patent citation network. The technological evolutionary trajectories of data mining domain are extracted. The experimental results show that the trajectories include innovation, diffusion, and breakthrough. It is a process combining incremental innovation with fundamental breakthrough. From the perspective of patent content, the top evolutionary path is divided into three sections. The technological development of each section is analyzed based on inheritance and continuity. Finally, the further research work is prospected.
Key words
technological evolutionary trajectory /
patent citation network /
connectivity analysis /
data mining
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
References
[1] Hummon N P and Doreain P. Connectivity in a citation network: the development of DNA theory [J]. Social Networks, 1989, (11): 39-63.
[2] Mina A, Ramlogan R, Tampubolon G and Metcalfe J S. Mapping evolutionary trajectories: Applications to the growth and transformation of medical knowledge [J]. Research Policy, 2007, 36(5): 789-806.
[3] 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.
[4] Jaffe A B and Trajtenberg M. Patents, citations and innovations: a window on the knowledge economy [M]. Cambridge, MA: MIT Press, 2002.
[5] Breitzman A F and Mogee M E. The many applications of patent analysis [J]. Journal of Information Science, 2002, 28(3): 187-205.
[6] Griliches Z. Patent statistics as economic indicators: A survey [J]. Journal of Economic Literature, 1990, 28(4): 1661-1707.
[7] Liu Li and Wang Yaode(刘立, 王耀德). The important role of public science in technological innovation: from the patent citation analysis perspective(从专利引文看公共科学对技术创新的重要作用) [J]. Studies in Science of Science(科学学研究), 2003, 21(4): 428-432.
[8] Kang Yuhang and Su Jingqin(康宇航, 苏敬勤). Technology tracking system based on patent quotation—theory model and tool development(基于专利引文的技术跟踪系统—理论模型与工具开发) [J]. Science of Science and Management of Science and Technology(科学学与科学技术管理), 2008(4): 24-27.
[9] United States Patent and Trademark Office [EB/OL]. [2011-07-25]. http://patft.uspto.gov/.
[10] Hall B H, Jaffe A B and Trajtenberg M. The NBER patent citation data file: lessons, insights and methodological tools [J]. NBER Working Paper 8498, 2001.
[11] Nooy W D, Mrvar A, Batagelj V. Exploratory network analysis with pajek [M]. Cambridge, MA: Cambridge University Press, 2005.
PDF(1394 KB)
