| Summary: | 碩士 === 國立嘉義大學 === 生物事業管理學系研究所 === 103 === Abstract
Resulting in product life cycles becoming ever shorter and global competitiveness, many companies or organizations have forced to invest significant resources in research and development (R&;D) activities. Therefore, a systematic and efficient approach of identifying technology trends and evolutionary potentials can help companies and organizations wisely allocate their resources and formulate their R&;D planning. But, traditionally approach is disadvantageous. Interaction between scientific knowledge and technical knowledge from each other. Advance in science knowledge as technology knowledge opens new growth. Therefore, This study proposed a framework combining the evolutionary trends by TRIZ and text-mining with science and technology publications to systematically identify technology trends from papers and patents. As technological information in paper documents and patent documents is stored almost entirely in non-structured text format, so text mining method can allow R&;D personnel to efficiently analysis technology information and effectively conduct R&;D planning; TRIZ theory is a systematic method that can help R&;D personnel limited experience constraints. Cardiovascular disease is one of the major diseases of people, and the rise of the medical equipment industry, so that the ECG sensor provides innovative opportunities for the future. So this study applies the proposed approach to explore the technology evolution trends of ECG sensor. Clustering results and identifying technological trends by experts, the results show in passage of time, only part of technology trends, such as“Geometric evolution of linear constructions”,“nested up”,“Decreasing human involvement”to reach a mature stage, rest of science and technology clusters has connected in some technology trends, such as“reducing system complexity”,“Mono-bi-poly-Similar objects”,“Mono-bi-poly-Various objects” belongs to the growth stage.
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