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논문 기본 정보

자료유형
학술저널
저자정보
박영현 (경남대학교) 이재호 (성균관대학교) 김경우 (양산발전연구원)
저널정보
한국무역학회 무역학회지 貿易學會誌 第46卷 第5號
발행연도
2021.10
수록면
65 - 81 (17page)

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표지
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연구주제
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연구배경
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연구방법
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연구결과
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초록· 키워드

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The technological development in the era of the 4th industrial revolution is changing the paradigm of various industries. Various technologies such as big data, cloud, artificial intelligence, virtual reality, and the Internet of Things are used, creating synergy effects with existing industries, creating radical development and value creation. Among them, the logistics sector has been greatly influenced by quantitative data from the past and has been continuously accumulating and managing data, so it is highly likely to be linked with big data analysis and has a high utilization effect. The modern advanced technology has developed together with the data mining technology to discover hidden patterns and new correlations in such big data, and through this, meaningful results are being derived. Therefore, data mining occupies an important part in big data analysis, and this study tried to analyze data mining techniques that can contribute to the logistics field and common logistics using these data mining technologies.
Therefore, by using the AHP technique, it was attempted to derive priorities for each type of efficient data mining for logisticalization, and R program and R Studio were used as tools to analyze this. Criteria of AHP method set association analysis, cluster analysis, decision tree method, artificial neural network method, web mining, and opinion mining. For the alternatives, common transport and delivery, common logistics center, common logistics information system, and common logistics partnership were set as factors.

목차

Abstract
Ⅰ. 서론
Ⅱ. 빅데이터 마이닝
Ⅲ. 연구모형의 설계
Ⅳ. 연구 결과 및 분석
Ⅴ. 결론
References

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