DATA MINING ANALYTICS FUNDAMENTALS AND THEIR APPLICATION IN LOGISTICS

Krzysztof Juliusz Wojtkowiak

DOI: http://dx.doi.org/10.12775/AUNC_ZARZ.2020.1.005

Abstrakt


The article describes several basic data mining fundamentals and their application in logistics and it consists of two sections. The first one is a description of different parts of data mining process: preparing the input data, completing the missing data, classification method using k-nearest neighbours algorithm with theoretical examples of usage conducted in open-source software called R and Weka. The second section of the article focuses on theoretical application of data mining methods in logistics, mainly in solving transportation problems and enhancing customer’s satisfaction. This section was strongly influenced by data provided by DHL enterprise report on Big Data. The data used in theoretical examples is of own elaboration.

Słowa kluczowe


logistyka; data mining

Pełny tekst:

PDF (English)

Bibliografia


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ISSN (print) 1689-8966
ISSN (online) 2450-7040

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Action funded by the Ministry of Science and Higher Education under the contract number 916/P-DUN/2019 by funds dedicated to dissemination of research findings. Preparing for publication papers in English and employing reviewers affiliated in research institutions abroad in 8 issues of the journal Acta Universitatis Nicolai Copernici Zarządzanie in 2019-2020: Vol. 46, No. 1-4 (2019), Vol. 47, No. 1-4 (2020)

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