Deriving technology intelligence from patents: Preposition-based semantic analysis

被引:55
作者
An, Jaehyeong [1 ]
Kim, Kyuwoong [2 ]
Mortara, Letizia [3 ]
Lee, Sungjoo [2 ]
机构
[1] Hyundai NGV, Technol Intelligence Team, Gwanak Ro 1, Seoul 08826, South Korea
[2] Ajou Univ, Dept Ind Engn, Worldcup Ro 206, Suwon 16499, South Korea
[3] Univ Cambridge, Dept Engn, Inst Mfg, Ctr Technol Management, Alan Reece Bldg,17 Charles Babbage Rd, Cambridge CB3 0FS, England
基金
新加坡国家研究基金会;
关键词
Technology intelligence; Technology search; Technology trends; Patent analysis; Semantic; Preposition; Text mining; Key-words; RESEARCH-AND-DEVELOPMENT; SOCIAL NETWORK ANALYSIS; TEXT-MINING APPROACH; INFORMATION; IDENTIFICATION; STRATEGY; TRENDS; INDICATORS; INNOVATION; DOCUMENTS;
D O I
10.1016/j.joi.2018.01.001
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Patents are one of the most reliable sources of technology intelligence, and the true value of patent analysis stems from its capability of describing the content of technology based on the relationships between keywords. To date a number of techniques for analyzing the information contained in patent documents that focus on the relationships between keywords have been suggested. However, a drawback of the existing keyword approaches is that they cannot yet determine the types of relationships between the keywords. This study proposes a novel approach based on preposition semantic analysis network which overcomes the limitations of the existing keywords-based network analysis and demonstrates its potential through an application. A preposition is a word that defines the relationship between two neighboring words, and, in the case of patents, prepositions aid in revealing the relationships between keywords related to technologies. To demonstrate the approach, patents regarding an electric vehicle were employed. 13 prepositions were identified which could be used to define 5 relationships between neighboring technological terms: "inclusion (utilization)," "objective (purpose)," "effect," "process," and "likeness." The proposed approach is expected to improve the usability of keyword-based patent analyses and support more elaborate studies on patent documents. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:217 / 236
页数:20
相关论文
共 57 条
[1]  
[Anonymous], 2004, The Journal of High Technology Management Research, DOI [10.1016/j.hitech.2003.09.003, DOI 10.1016/J.HITECH.2003.09.003]
[2]  
[Anonymous], MANAGEMENT TECHNOLOG
[3]   The innovative performance of in-house and contracted R&D in terms of patents and utility models [J].
Beneito, P .
RESEARCH POLICY, 2006, 35 (04) :502-517
[4]   Evaluating the risk of patent infringement by means of semantic patent analysis: the case of DNA chips [J].
Bergmann, Isumo ;
Butzke, Daniel ;
Walter, Lothar ;
Fuerste, Jens P. ;
Moehrle, Martin G. ;
Erdmann, Volker A. .
R & D MANAGEMENT, 2008, 38 (05) :550-562
[5]   A relational view of information seeking and learning in social networks [J].
Borgatti, SP ;
Cross, R .
MANAGEMENT SCIENCE, 2003, 49 (04) :432-445
[6]   Network Analysis in the Social Sciences [J].
Borgatti, Stephen P. ;
Mehra, Ajay ;
Brass, Daniel J. ;
Labianca, Giuseppe .
SCIENCE, 2009, 323 (5916) :892-895
[7]   The Emerging Clusters Model: A tool for identifying emerging technologies across multiple patent systems [J].
Breitzman, Anthony ;
Thomas, Patrick .
RESEARCH POLICY, 2015, 44 (01) :195-205
[8]  
Cascini G, 2004, LECT NOTES COMPUT SC, V3163, P508
[9]   Identifying missing relevant patent citation links by using bibliographic coupling in LED illuminating technology [J].
Chen, Dar-Zen ;
Huang, Mu-Hsuan ;
Hsieh, Hui-Chen ;
Lin, Chang-Pin .
JOURNAL OF INFORMETRICS, 2011, 5 (03) :400-412
[10]  
Chen L., 2003, ASS COMPUTATIONAL LI