Article (Scientific journals)
A Survey of Information Entropy Metrics for Complex Networks
Omar, Yamila; Plapper, Peter
2020In Entropy
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Keywords :
complex networks; entropy; centrality; Shannon's entropy
Abstract :
[en] Information entropy metrics have been applied to a wide range of problems that were abstracted as complex networks. This growing body of research is scattered in multiple disciplines, which makes it difficult to identify available metrics and understand the context in which they are applicable. In this work, a narrative literature review of information entropy metrics for complex networks is conducted following the PRISMA guidelines. Existing entropy metrics are classified according to three different criteria: whether the metric provides a property of the graph or a graph component (such as the nodes), the chosen probability distribution, and the types of complex networks to which the metrics are applicable. Consequently, this work identifies the areas in need for further development aiming to guide future research efforts.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Omar, Yamila ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)
Plapper, Peter ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)
External co-authors :
no
Language :
English
Title :
A Survey of Information Entropy Metrics for Complex Networks
Publication date :
15 December 2020
Journal title :
Entropy
ISSN :
1099-4300
Publisher :
Multidisciplinary Digital Publishing Institute (MDPI), Basel, Switzerland
Peer reviewed :
Peer Reviewed verified by ORBi
FnR Project :
FNR11601404 - Business Analytics In Manufacturing: Husky Solutioning Lead-time Optimization, 2017 (01/03/2017-31/07/2021) - Yamila Omar
Funders :
FNR - Fonds National de la Recherche [LU]
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