Building potential patent portfolios: An integrated approach based on topic identification and correlation analysis

NSL OpenIR > Journal of Data and Information Science > Chinese Journal of Library and Information Science-2015

	Building potential patent portfolios: An integrated approach based on topic identification and correlation analysis
	ZHANG Xian1,2 ; XU Haiyun1 ; FANG Shu2 ; HU Zhengyin1 ; LI Shuying1,2 ; Xian Zhang (E-mail: zhangx@clas.ac.cn).
	2015-06-27
发表期刊	Chinese Journal of Library and Information Science
卷号	8 期号:2 页码:39-51
摘要	Purpose: This paper suggests a framework to identify important patents for building potential patent portfolios based on patents owned by different assignees so as to highlight the value of individual patents in technology transfer and identify potential collaborators for patent assignees. Design/methodology/approach: The analysis framework includes the following steps: 1) co-classification analysis based on the International Patent Classification (IPC) codes and Derwent Manual Codes (DMC) to detect sub-tech fields, 2) keyword co-occurrence analysis aiming to understand the core technology information in each patent, and 3) social network analysis used for identifying important technologies and partnerships of key assignees. A case study was conducted with 27,401 chemistry patents filed by a Chinese national research institute. Findings: The results show that this framework is effective in building potential technological patent portfolios based on patents owned by different assignees and identifying future collaborators for the assignees. This integrated approach based on topic identification and correlation analysis that combines network-based analysis with keyword-based analysis can reveal important patented technologies and their connections and help understand detailed technological information mentioned in patents. Research limitations: In keywords analysis, only titles and abstracts of patent documents were used and weights of keywords in different parts of the documents were not considered. Practical implications: The analysis framework provides valuable information for decisionmakers of large institutions which have many patents with broad application prospects. Originality/value: Different from previous patent portfolio studies based on the use of a combination of patent analysis indicators, this study provides insights into a method of building patent portfolios to discover the potential of individual patents in technology transfer and promote cooperation among different patent assignees. ; Purpose: This paper suggests a framework to identify important patents for building potential patent portfolios based on patents owned by different assignees so as to highlight the value of individual patents in technology transfer and identify potential collaborators for patent assignees. Design/methodology/approach: The analysis framework includes the following steps: 1) co-classification analysis based on the International Patent Classification (IPC) codes and Derwent Manual Codes (DMC) to detect sub-tech fields, 2) keyword co-occurrence analysis aiming to understand the core technology information in each patent, and 3) social network analysis used for identifying important technologies and partnerships of key assignees. A case study was conducted with 27,401 chemistry patents filed by a Chinese national research institute. Findings: The results show that this framework is effective in building potential technological patent portfolios based on patents owned by different assignees and identifying future collaborators for the assignees. This integrated approach based on topic identification and correlation analysis that combines network-based analysis with keyword-based analysis can reveal important patented technologies and their connections and help understand detailed technological information mentioned in patents. Research limitations: In keywords analysis, only titles and abstracts of patent documents were used and weights of keywords in different parts of the documents were not considered. Practical implications: The analysis framework provides valuable information for decisionmakers of large institutions which have many patents with broad application prospects. Originality/value: Different from previous patent portfolio studies based on the use of a combination of patent analysis indicators, this study provides insights into a method of building patent portfolios to discover the potential of individual patents in technology transfer and promote cooperation among different patent assignees.
文章类型	Research Papers
关键词	Patent Portfolio Patent Cooperation Topic Identification Correlation Analysis Social Network Analysis (Sna)
学科领域	新闻学与传播学 ; 图书馆、情报与文献学
URL	查看原文
收录类别	其他
所属项目编号	Grant No.: KFJ-EW-STS-032 ; Grant No.: Y4C0091001 ; Grant No.: 14CTQ033
语种	英语
项目资助者	This work is jointly supported by the Science and Technology Service Network Initiative of Chinese Academy of Sciences ; West Light Foundation of Chinese Academy of Sciences ; National Social Science Foundation of China
文献类型	期刊论文
条目标识符	http://ir.las.ac.cn/handle/12502/7809
专题	Journal of Data and Information Science_Chinese Journal of Library and Information Science-2015
通讯作者	Xian Zhang (E-mail: zhangx@clas.ac.cn).
作者单位	1.Chengdu Library, Chinese Academy of Sciences, Chengdu 610041, China 2.University of Chinese Academy of Sciences, Beijing 100190, China
第一作者单位	中国科学院文献情报中心
推荐引用方式 GB/T 7714	ZHANG Xian,XU Haiyun,FANG Shu,et al. Building potential patent portfolios: An integrated approach based on topic identification and correlation analysis[J]. Chinese Journal of Library and Information Science,2015,8(2):39-51.
APA	ZHANG Xian,XU Haiyun,FANG Shu,HU Zhengyin,LI Shuying,&Xian Zhang .(2015).Building potential patent portfolios: An integrated approach based on topic identification and correlation analysis.Chinese Journal of Library and Information Science,8(2),39-51.
MLA	ZHANG Xian,et al."Building potential patent portfolios: An integrated approach based on topic identification and correlation analysis".Chinese Journal of Library and Information Science 8.2(2015):39-51.

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