학술논문
DTW-kNN 기반의 유망 기술 식별을 위한 의사결정 지원 시스템 구현 방안
Implementation of DTW-kNN-based Decision Support System for Discriminating Emerging Technologies
Implementation of DTW-kNN-based Decision Support System for Discriminating Emerging Technologies
Document Type
Article
Text
Text
Author
Source
산업융합연구(구 대한산업경영학회지), 08/31/2022, Vol. 20, Issue 8, p. 77-84
Subject
Language
한국어(KOR)
ISSN
2635-8875
Abstract
This study aims to present a method for implementing a decision support system that can be used for selecting emerging technologies by applying a machine learning-based automatic classification technique. To conduct the research, the architecture of the entire system was built and detailed research steps were conducted. First, emerging technology candidate items were selected and trend data was automatically generated using a big data system. After defining the conceptual model and pattern classification structure of technological development, an efficient machine learning method was presented through an automatic classification experiment. Finally, the analysis results of the system were interpreted and methods for utilization were derived. In a DTW-kNN-based classification experiment that combines the Dynamic Time Warping(DTW) method and the k-Nearest Neighbors(kNN) classification model proposed in this study, the identification performance was up to 87.7%, and particularly in the ‘eventual’ section where the trend highly fluctuates, the maximum performance difference was 39.4% points compared to the Euclidean Distance(ED) algorithm. In addition, through the analysis results presented by the system, it was confirmed that this decision support system can be effectively utilized in the process of automatically classifying and filtering by type with a large amount of trend data.