Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/267183 
Year of Publication: 
2022
Citation: 
[Editor:] Kersten, Wolfgang [Editor:] Jahn, Carlos [Editor:] Blecker, Thorsten [Editor:] Ringle, Christian M. [Title:] Changing Tides: The New Role of Resilience and Sustainability in Logistics and Supply Chain Management – Innovative Approaches for the Shift to a New Era. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 33 [ISBN:] 978-3-756541-95-9 [Publisher:] epubli GmbH [Place:] Berlin [Year:] 2022 [Pages:] 91-117
Publisher: 
epubli GmbH, Berlin
Abstract: 
Purpose: Our research emphasizes the importance of considering outliers in production logistics tasks. With a growing amount of data, we require data mining to cope with these tasks. We underline that the widespread exclusion of outliers in data pre-processing for data mining leads to a loss of information and that using outlier interpretation can be used to address the issue. Methodology: The paper discusses the data pre-processing of data mining in production logistics problems. Methods of outlier interpretation are collected based on a literature review. In addition to the literature-based investigation, the work relies on a case study that illustrates the individual evaluation of outliers. Findings: This work shows that outliers take a special focus on the information generation. Within data pre-processing, a distinction must be made between an outlier as a defect and an outlier as a special datum. This can be conducted by methods presented in the literature. Originality: This paper adds to existing literature in the research field of insufficiently analyzed outlier interpretation and shows a need for research in data pre-processing of data mining.
Subjects: 
Advanced Manufacturing
Industry 4.0
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-sa Logo
Document Type: 
Conference Paper

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