The study of applying co-occurrence of classification symbols in detecting the technology evolvement in US Cancer Moonshot related patents

• Main Authors: Wei-Ming Tu, 杜維民
• Other Authors: Chung-Huei Kuan
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/cn2aq2

碩士 === 國立臺灣科技大學 === 專利研究所 === 106 === Technology development is a circulation process combined with initiation and fusion; along with the advance of basic science research that various academic disciplines interact with each other and stimulate the birth of cross-field knowledge and emerging subjects prompted all time. Thus, there is a need to develop a reliable method to illustrate the profile of knowledge and technology precisely. To better research and development, that enterprise must rely on accurate evaluation for competitors, knowing its own location in the field and be award of the focus of R&D to help making decisions. Classification symbol is essential patent analysis resource. It’s assigned by professional examiner after reading and realizing the connotation of patent application. Since classification symbol is the bibliographic data which reflect the connotation of technology, there are tremendous research applies both in theory or practice affairs. While multiple classification symbols being recorded in a single patent literature which reflect the various innovation features, that one can perform co-occurrence analysis combined with time factor to illustrate the history and trajectory of certain technology field. In the study we analyze the classification symbol for Cancer Moonshot dataset released by USPTO. The definition of classification symbol co-occurrence analysis is that by performing the technic of statistic, computer science and bibliometrics, to mine the hidden connection between classification symbols in patent literatures. Our study tries to illustrate the unique evolve history and direction in a certain period of specific technology filed & present the procedure with data visualization. In our study, we show that A61K31-related technology had always been the focus of R&D in cancer-drug treatment in the dataset; For both existing or emerging classification symbol, they are always center on A61K31, while the number of combination of A61K47 and C07K16 grow significantly; indicating that observing the field of drug treatment for cancer, focusing in the group that highly co-occurrence with it may reflect the technical trend. In the study we provide a method of utilizing classification symbol to help enterprise, research facility and school to keep abreast of new technology developments and making decision.