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Big Data Analytics and Fuzzy Technology: Extracting Information from Social Data Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Decomposable Graphical Models on Learning, Fusion and Revision

Authors : Fabian Schmidt, Jörg Gebhardt, Rudolf Kruse

Published in: Recent Developments and the New Direction in Soft-Computing Foundations and Applications

Publisher: Springer International Publishing

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Abstract

Industrial applications often face elaborated problems. In order to solve them properly a great deal of complexity and data diversity has to be managed. In this paper we present a planning system that is used globally by the Volkswagen Group. We introduce the specific challenges that this industrial application faces, namely a high complexity paired with diverse heterogeneous data sources, and describe how the problem has been modelled and solved. We further introduce the core technology we used, the revision of Markov networks. We further motivate the need to handle planning inconsistencies and present our framework consisting of six main components: Prevention, Detection, Analysis, Explanation, Manual Resolution, and Automatic Elimination.

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previous chapter Bilingual Students Benefit from Using Both Languages
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Metadata
Title
Decomposable Graphical Models on Learning, Fusion and Revision
Authors
Fabian Schmidt
Jörg Gebhardt
Rudolf Kruse
Copyright Year
2018
Book
Recent Developments and the New Direction in Soft-Computing Foundations and Applications

Print ISBN: 978-3-319-75407-9

Electronic ISBN: 978-3-319-75408-6

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-75408-6_34

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