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https://doi.org/10.31224/4887...
Article . 2025 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Multidimensional HyperNetwork and Multidimensional SuperHyperNetwork

Authors: Takaaki Fujita;

Multidimensional HyperNetwork and Multidimensional SuperHyperNetwork

Abstract

Graph theory studies the mathematical structures of vertices and edges to model relationships and connectivity [1, 2]. Hypergraphs extend this framework by allowing hyperedges to connect arbitrarily many vertices at once [3], and superhypergraphs further generalize hypergraphs via iterated powerset constructions to capture hierarchical linkages among edges [4,5]. Weighted multidimensional networks model nodes connected by edges in multiple layers, assigning each edge a weight to quantify relationship strength in its specific dimension(cf. [6,7]). In this paper, we extend these ideas using hypergraphs and superhypergraphs to introduce and formalize multidimensional hypernetworks and multidimensional superhypernetworks.

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
hybrid