Identifying New Technology Opportunities:How to look inside patent vacancies
Despite being a strong stimulus for identifying new technology opportunities, the previously suggested patent maps are subject to certain limitations of being non-quantitative and vague methods. Thus, the conventional approaches typically do not provide practical technology opportunities. This study proposes an intelligent approach to generating a patent map and assessing the validity of patent vacancies. Involving many methods and complex algorithms may lead to conceptual misunderstanding and imprecise use in practice, so the suggested model is designed to be executed in four discrete steps: data collection and preprocessing; using morphology analysis (MA) and semantic text analysis (STA) to configure patented inventions; using principal component analysis (PCA) to generate a patent map; and using rough set theory (RST) to assess the validity of patent vacancies. We believe our method can be employed in various research areas, such as intellectual property management and R&D screening, as well as serving as a starting point for developing a more general model.
technology opportunity analysis patent vacancy technology intelligence morphology analysis (MA) semantic text analysis (STA) principal component analysis (PCA) rough set theory (RST)
Changyong Lee Seungkyum Kim Yongyoon Suh Hyeonju Seol
Department of Industrial Engineering Seoul National University Seoul, Republic of Korea Department of Systems Engineering Korea Air Force Academy Chungbuk, Republic of Korea
国际会议
重庆
英文
157-161
2011-01-21（万方平台首次上网日期，不代表论文的发表时间）