ScholarWorks@동국대학교

초록

Science and technology are crucial elements in discovering innovation opportunities. They have their own practical and theoretical unique meaning in innovation factors. Scientific or techno-logical information can be collected by patents or papers, and various approaches for innovation opportunities discovery are being proposed using text mining. Since a previous methodology using patents and papers discovered opportunities in science or technology itself, they cannot discover opportunities reflecting the science and technology relationship. In addition, since dis-covered innovation opportunities are formed within the keyword or phrase level, they cannot provide innovation direction or purpose. Therefore, this study suggests a new approach to dis-covering science and technology innovation opportunities that reflects the science-technology relationship and their concrete directions/purposes using the sentence generation algorithm. An algorithm-generated sentence can contain contextual flow and connection between keywords. In contrast, the generated sentences from the sentence model can reflect science and technology from mass data in a readable sentence. Key innovation factors from science and technology are extracted from generated sentences and then innovation opportunities with specific directions and purposes are suggested.

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