This item is licensed Korea Open Government License
dc.contributor.author
김진형
dc.contributor.author
정도헌
dc.contributor.author
이미경
dc.contributor.author
이승우
dc.contributor.author
정한민
dc.contributor.author
황명권
dc.date.accessioned
2019-08-28T07:41:17Z
dc.date.available
2019-08-28T07:41:17Z
dc.date.issued
2013-02-01
dc.identifier.issn
1343-4500
dc.identifier.uri
https://repository.kisti.re.kr/handle/10580/14129
dc.description.abstract
Analyzing mass information and supporting future insight based on analysis results are very important work but it requires much effort and time. Information analysis and future predictions about the science and IT field data are also very critical tasks for researchers, government officers, businessman, etc. Therefore, in this paper, we propose a technology opportunity discovery (TOD) model based on feature selection and decision making for effective, systematic, and objective information analysis and future forecasting in the science and IT fields. In addition, we execute a comparative evaluation between the suggested TOD model and Gartne forecasting model for validating the suggested model.