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구분 SCI
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학술지 Understanding Postal Delivery Areas in the Republic of Korea Using Multiple Unsupervised Learning Approaches
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저자
한기준, 유영웅, 나동길, 정훈, 허영교, 정현철, 윤성욱, 김정은
발행일
202204
출처
ETRI Journal, v.44 no.2, pp.232-243
ISSN
1225-6463
출판사
한국전자통신연구원 (ETRI)
DOI
https://dx.doi.org/10.4218/etrij.2021-0407
협약과제
21HR3300, 우편물류 인프라 기술개발, 정훈
초록
Changes in household composition and the residential environment have had a considerable impact on the features of postal delivery regions in recent years, resulting in a large increase in the overall workload of domestic postal delivery services. In this paper, we provide complex analysis results for postal delivery areas using various unsupervised learning approaches. First, we extract highly influential features using several feature-engineering methods. Then, using quantitative and qualitative cluster analyses, we find the distinctive traits and semantics of postal delivery zones. Unsupervised learning approaches are useful for successfully grouping postal service zones, according to our findings. Furthermore, by comparing a postal delivery region to other areas in the same group, workload balancing was achieved.
키워드
clustering, feature engineering, postal delivery management, unsupervised learning, workload balancing
KSP 제안 키워드
Complex analysis, Delivery management, Engineering Methods, Learning approach, Republic of Korea, Workload Balancing, cluster analyses, feature engineering, residential environment, unsupervised learning
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