earticle

영어

In the feasibility analysis of R&D program, the data used to analyze the impact/trends/level of technology derive mostly from patents and theses. However, there is limitation in reflecting the newest technology trends data based on patents and theses. That is because of the occurrence of a one or two year gap time before these patents(or theses)are actually published or granted. Therefore, not only are related patents and theses data collected but, the extensive trends data from public web sites and social networks also need to be collected and analyzed. It takes a great deal of time, and manpower for these related feasibility analysis to happen successfully. To solve this issue, this analysis presents a methodology not only to rapidly and accurately collect data but, to efficiently analyze the newest technology trend flows. To analyze technology impact, phases of the data extraction, the application of measuring model and the determination of TIIB (Technology Impact Index based on Big Data) are processed. This theses proposes that the data analysis methodology used to find out the latest technology trends could also be useful for optimizing efficiency when analyzing. Moreover, the newly developed TIIB enables us to check the interest trends of the technology by reading the yearly changes.