An SAO-based text mining approach to building a technology tree for technology planning

Authors:
Sungchul Choi;Hyunseok Park;Dongwoo Kang;Jae Yeol Lee;Kwangsoo Kim
Affiliations:
CTO Office, Samsung Advanced Institute of Technology Mt. 14-1, Nongseo-dong, Giheung-gu, Yongin-si Gyeonggi-do, 446-712, Republic of Korea;Department of Technology and Innovation Management, Pohang University of Science and Technology, San 31, Hyoja-dong, Nam-gu, Pohang, 790-784, Republic of Korea;Department of Industrial and Management Engineering, Pohang University of Science and Technology, San 31, Hyoja-dong, Nam-gu, Pohang, Kyungbuk 790-784, Republic of Korea;Department of Industrial Engineering, Chonnam National University, 77 Yongbong-ro, Buk-gu, Gwangju 500-757, Republic of Korea;Department of Industrial and Management Engineering, Pohang University of Science and Technology, San 31, Hyoja-dong, Nam-gu, Pohang, Kyungbuk 790-784, Republic of Korea
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

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Abstract

A technology tree (TechTree) is a branching diagram that expresses relationships among product components, technologies, or functions of a technology in a specific technology area. A TechTree identifies strategic core technologies and is a useful tool to support decision making in a given market environment for organizations with specified capabilities. However, existing TechTrees generally overemphasize qualitative and expert-dependent knowledge rather than incorporating quantitative and objective information. In addition, the traditional process of developing a TechTree requires vast amounts of information, which costs considerably in terms of time, and cannot provide integrated information from a variety of technological perspectives simultaneously. To remedy these problems, this research presents a text mining approach based on Subject-Action-Object (SAO) structures; this approach develops a TechTree by extracting and analyzing SAO structures from patent documents. The extracted SAO structures are categorized by similarities, and are identified by the type of technological implications. To demonstrate the feasibility of the proposed approach, we developed a TechTree regarding Proton Exchange Fuel Cell technology.