Title :
Towards Discovering Emerging Technologies Based on Decision Tree
Author :
Lee, Jinhee ; Kim, Jinhyung ; Lee, Seungwoo ; Seo, Dongmin ; Jung, Hanmin ; Sung, Won-Kyung
Abstract :
It becomes important to discover technical opportunity when we due to uncertainties about forecast. As the internet grows rapidly and the amount of information in the web increases exponentially, however, analysis and forecast regarding the science and technology become more difficult. Because decision of emerging technology needs much cost and time, we need more effective method and solution for decision making of prospective science technologies. For overcoming the above limitations, many methods based on non-systemic processes such as Delphi and Scenario technique was suggested. However, the solutions based on non-systemic processes can not sure accuracy of results and show inconsistent forecasting about the science technology. Therefore we propose the systematic and scientific model for analyzing science technologies and forecasting the emerging technologies in this papers. We obtain features using existing technology lifecycle model and make decision tree model consisted of extracted features. In order to evaluate this model, we did performance test toward 50 technologies in Gartner´s Hype cycle for emerging technologies 2009~2010, and can get accuracy of 84%.
Keywords :
decision making; decision trees; technological forecasting; Delphi; Gartner hype cycle; decision making; decision tree; emerging technology discovery; emerging technology forecasting; nonsystemic process; prospective science technology; scenario technique; technology lifecycle model; Accuracy; Analytical models; Decision making; Decision trees; Feature extraction; Forecasting; Patents; Decision Making; Decision Tree; Emerging Technology; Technical Opportunity; Technology Lifecycle;
Conference_Titel :
Internet of Things (iThings/CPSCom), 2011 International Conference on and 4th International Conference on Cyber, Physical and Social Computing
Conference_Location :
Dalian
Print_ISBN :
978-1-4577-1976-9
DOI :
10.1109/iThings/CPSCom.2011.91