초록

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Abstract ▼ AI-Helper

As recently the interest in the future industry grows high, the demand for forecasting the future shape of science and technology, especially exploring 'weak signals' of changes in science and technology, increases as well. The 'weak signals' means that currently they are uncertain and abnormal sign...

As recently the interest in the future industry grows high, the demand for forecasting the future shape of science and technology, especially exploring 'weak signals' of changes in science and technology, increases as well. The 'weak signals' means that currently they are uncertain and abnormal signals, but are preliminary signals which might lead future changes. Accordingly they can provide important clues to the future forecast. The study of 'weak signals' has its significance in providing important clues to the projection of the future technology earlier. As it has not a long history from its concept to exploration methods to utilization, more intensive study is required. Exploring 'weak signals' has been conducted mainly through the information analysis by experts with a high level of intelligence and sense. However, such an analysis is difficult and broad in scope, and furthermore the interpretation of analysis results is very limited, relying primarily on the decision of experts themselves. The purpose of this study is to provide a more objectified way to support these expert-based tasks. It derives quantitative results from non-structured article information and provides a logical basis for detecting the signals based on the results.

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