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Title: Building potential patent portfolios: An integrated approach based on topic identification and correlation analysis
Author: Zhang, Xian(张娴)1,2; Hai-yun Xu(许海云)1; Shu Fang(方曙)2; Hu, ZhengYin(胡正银)1; Li Shuying(李姝影)1,2
Source: Chinese Journal of Library and Information Science
Issued Date: 2015-06-27
Volume: 8, Issue:2, Pages:39-51
Keyword: Patent portfolio ; Patent cooperation ; Topic identification ; Correlation analysis ; Social network analysis (SNA)
Subject: 新闻学与传播学 ; 图书馆、情报与文献学
Indexed Type: 其他
Corresponding Author: Xian Zhang (E-mail: zhangx@clas.ac.cn).
DOC Type: Research Papers
Abstract: 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.
English Abstract: 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.
Project Number: Grant No.: KFJ-EW-STS-032 ; Grant No.: Y4C0091001 ; Grant No.: 14CTQ033
Funder: 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
Related URLs: 查看原文
Language: 英语
Content Type: 期刊论文
URI: http://ir.las.ac.cn/handle/12502/7809
Appears in Collections:Chinese Journal of Library and Information Science-2015_期刊论文

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description.institution: 1.Chengdu Library, Chinese Academy of Sciences, Chengdu 610041, China
2.University of Chinese Academy of Sciences, Beijing 100190, China

Recommended Citation:
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.
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