Results 21 to 30 of about 52,296 (256)
Signed random walk diffusion for effective representation learning in signed graphs.
PLoS ONE, 2022 How can we model node representations to accurately infer the signs of missing edges in a signed social graph? Signed social graphs have attracted considerable attention to model trust relationships between people. Various representation learning methods
Jinhong Jung, Jaemin Yoo, U Kang
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Further Results on the Nullity of Signed Graphs
Journal of Applied Mathematics, 2014 The nullity of a graph is the multiplicity of the eigenvalue zero in its spectrum. A signed graph is a graph with a sign attached to each of its edges. In this paper, we apply the coefficient theorem on the characteristic polynomial of a signed graph and
Yu Liu, Lihua You
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Research on Extreme Signed Graphs with Minimal Energy in Tricyclic Signed Graphs S(n, n + 2)
Complexity, 2020 A signed graph is acquired by attaching a sign to each edge of a simple graph, and the signed graphs have been widely used as significant computer models in the study of complex systems.
Yajing Wang, Yubin Gao
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Learning Weight Signed Network Embedding with Graph Neural Networks
Data Science and Engineering, 2023 Network embedding aims to map nodes in a network to low-dimensional vector representations. Graph neural networks (GNNs) have received much attention and have achieved state-of-the-art performance in learning node representation.
Zekun Lu +4 more
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On $bullet$-lict signed graphs $L_{bullet_c}(S)$ and $bullet$-line signed graphs $L_bullet(S)$ [PDF]
Transactions on Combinatorics, 2016 A emph{signed graph} (or, in short, emph{sigraph}) $S=(S^u,sigma)$ consists of an underlying graph $S^u :=G=(V,E)$ and a function $sigma:E(S^u)longrightarrow {+,-}$, called the signature of $S$. A emph{marking} of $S$ is a function $mu:V(S)longrightarrow
Mukti Acharya +2 more
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Signed Complete Graphs with Maximum Index
Discussiones Mathematicae Graph Theory, 2020 Let Γ = (G, σ) be a signed graph, where G is the underlying simple graph and σ E(G) → {−, +} is the sign function on the edges of G. The adjacency matrix of a signed graph has −1 or +1 for adjacent vertices, depending on the sign of the edges.
Akbari Saieed +3 more
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Notes on upper bounds for the largest eigenvalue based on edge-decompositions of a signed graph
Kuwait Journal of Science, 2023 The adjacency matrix of a signed graph has +1 or -1 for adjacent vertices, depending on the sign of the connecting edge. According to this concept, an ordinary graph can be interpreted as a signed graph without negative edges.
Zoran Stanić
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Improved kernels for Signed Max Cut parameterized above lower bound on (r,l)-graphs [PDF]
Discrete Mathematics & Theoretical Computer Science, 2017 A graph $G$ is signed if each edge is assigned $+$ or $-$. A signed graph is balanced if there is a bipartition of its vertex set such that an edge has sign $-$ if and only if its endpoints are in different parts.
Luerbio Faria +3 more
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Ain Shams Engineering JournalThis paper presents an algorithm to compute the integrity of a signed fuzzy graph by systematically evaluating vertex subsets, removing them, and analyzing the resulting connected components.
Chakaravarthy Sankar +3 more
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Eigenspaces for \(-2\) in signed line graphs
The American Journal of CombinatoricsIt is known that \(-2\) appears in the spectrum of a connected signed line graph if and only if its root is either (a) a balanced signed graph, not a tree, that spans a switching of the complete signed graph or (b) an unbalanced simply signed graph ...
Zoran Stanić
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