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Open Source Analytics Solutions for Maintenance
VTT, Technical Research Centre of Finland Ltd., Finland.
Linnaeus University, Faculty of Technology, Department of Informatics.ORCID iD: 0000-0001-7048-8089
Indian Institute of Technology, India.
VTT, Technical Research Centre of Finland Ltd., Finland.
2018 (English)In: 2018 5th International Conference on Control, Decision and Information Technologies, CoDIT 2018, IEEE, 2018, p. 688-693Conference paper, Published paper (Refereed)
Abstract [en]

The current paper reviews existent data mining and big data analytics open source solutions. In the area of industrial maintenance engineering, the algorithms, which are part of these solutions, have started to be studied and introduced into the domain. In addition, the interest in big data and analytics have increased in several areas because of the increased amount of data produced as well as a remarkable speed attained and its variation, i.e.The so-called 3 V's (Volume, Velocity, and Variety). The companies and organizations have seen the need to optimize their decision-making processes with the support of data mining and big data analytics. The development of this kind of solutions might be a long process and for some companies something that is not within their reach for many reasons. It is, therefore, important to understand the characteristics of the open source solutions. Consequently, the authors use a framework to organize their findings. Thus, the framework used is called the knowledge discovery in databases (KDD) process for extracting useful knowledge from volumes of data. The authors suggest a modified KDD framework to be able to understand if the respective data mining/big data solutions are adequate and suitable to use in the domain of industrial maintenance engineering. © 2018 IEEE.

Place, publisher, year, edition, pages
IEEE, 2018. p. 688-693
Series
International Conference on Control Decision and Information Technologies, ISSN 2576-3555
Keywords [en]
big data, CBM, data mining, maintenance, open source, Decision making, Solution mining, Big Data Analytics, Big data and analytics, Data solutions, Decision making process, Knowledge discovery in database, Open sources, Open-source solutions
National Category
Computer Systems
Research subject
Computer and Information Sciences Computer Science, Information Systems
Identifiers
URN: urn:nbn:se:lnu:diva-83552DOI: 10.1109/CoDIT.2018.8394819ISI: 000468641000115Scopus ID: 2-s2.0-85050221189ISBN: 9781538650653 (print)OAI: oai:DiVA.org:lnu-83552DiVA, id: diva2:1318407
Conference
5th International Conference on Control, Decision and Information Technologies, CoDIT 2018, 10-13 April 2018, Thessaloniki, Greece
Available from: 2019-05-27 Created: 2019-05-27 Last updated: 2019-06-12Bibliographically approved

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Campos, Jaime

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Citation style
  • apa
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Output format
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