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We propose Graph Generating Dependencies (GGDs), a new class of dependencies for property graphs. Extending the expressivity of state of the art constraint languages, GGDs can express both tuple- and equality-generating dependencies on…

Databases · Computer Science 2020-06-16 Larissa C. Shimomura , George Fletcher , Nikolay Yakovets

We consider the problem of decomposing a given (di)graph into paths of length 2 with the additional restriction that no two such paths may have more than one vertex in common. We establish its NP-hardness by a reduction from 3-SAT,…

Discrete Mathematics · Computer Science 2019-07-12 Annika Thome , Matthias Walter

S-prime graphs are graphs that cannot be represented as nontrivial subgraphs of nontrivial Cartesian products of graphs, i.e., whenever it is a subgraph of a nontrivial Cartesian product graph it is a subgraph of one the factors. A graph is…

Computational Complexity · Computer Science 2017-05-11 Marc Hellmuth

A graph $G$ is said to be $d$-distinguishable if there is a labeling of the vertices with $d$ labels so that only the trivial automorphism preserves the labels. The smallest such $d$ is the distinguishing number, Dist($G$). A subset of…

Combinatorics · Mathematics 2024-06-13 Debra Boutin , Sally Cockburn

Convexity is a notion that has been defined for subsets of $\RR^n$ and for subsets of general graphs. A convex cut of a graph $G=(V, E)$ is a $2$-partition $V_1 \dot{\cup} V_2=V$ such that both $V_1$ and $V_2$ are convex, \ie shortest paths…

Data Structures and Algorithms · Computer Science 2014-01-17 Roland Glantz , Henning Meyerhenke

A tuple (s1,t1,s2,t2) of vertices in a simple undirected graph is 2-linked when there are two vertex-disjoint paths respectively from s1 to t1 and s2 to t2. A graph is 2-linked when all such tuples are 2-linked. We give a new and simple…

Data Structures and Algorithms · Computer Science 2025-08-15 Samuel Humeau , Damien Pous

Graphs are widely used as a popular representation of the network structure of connected data. Graph data can be found in a broad spectrum of application domains such as social systems, ecosystems, biological networks, knowledge graphs, and…

Machine Learning · Computer Science 2021-05-04 Feng Xia , Ke Sun , Shuo Yu , Abdul Aziz , Liangtian Wan , Shirui Pan , Huan Liu

Let $G$ be a finite, simple, and undirected graph of order $n$ and average degree $d$. Up to terms of smaller order, we characterize the minimal intervals $I$ containing $d$ that are guaranteed to contain some vertex degree. In particular,…

Combinatorics · Mathematics 2023-01-20 Johannes Pardey , Dieter Rautenbach

The power graph $P(G)$ of a finite group $G$ is the graph with vertex set $G$ and two distinct vertices are adjacent if either of them is a power of the other. Here we show that the power graph $P(G_1 \times G_2)$ of the direct product of…

Combinatorics · Mathematics 2016-06-24 A. K. Bhuniya , Sajal Kumar Mukherjee

A graph is called a chain graph if it is bipartite and the neighborhoods of the vertices in each color class form a chain with respect to inclusion. A threshold graph can be obtained from a chain graph by making adjacent all pairs of…

Combinatorics · Mathematics 2018-03-02 M. Anđelić , E. Ghorbani , S. K. Simić

Vector representations of graphs and relational structures, whether hand-crafted feature vectors or learned representations, enable us to apply standard data analysis and machine learning techniques to the structures. A wide range of…

Machine Learning · Computer Science 2020-03-31 Martin Grohe

A natural representation of random graphs is the random measure. The collection of product random measures, their transformations, and non-negative test functions forms a general representation of the collection of non-negative weighted…

Probability · Mathematics 2022-04-21 Caleb Bastian , Herschel Rabitz

We explore pseudometrics for directed graphs in order to better understand their topological properties. The directed flag complex associated to a directed graph provides a useful bridge between network science and topology. Indeed, it has…

Algebraic Topology · Mathematics 2021-07-26 Ana Lucia Garcia-Pulido , Kathryn Hess , Jane Tan , Katharine Turner , Bei Wang , Naya Yerolemou

It appeared recently that the classical random graph model used to represent real-world complex networks does not capture their main properties. Since then, various attempts have been made to provide accurate models. We study here a model…

Statistical Mechanics · Physics 2021-03-22 Jean-Loup Guillaume , Matthieu Latapy

A $k$-regular graph is called a divisible design graph if its vertex set can be partitioned into $m$ classes of size $n$, such that two distinct vertices from the same class have exactly $\lambda_1$ common neighbours, and two vertices from…

Combinatorics · Mathematics 2022-10-20 Dmitry Panasenko

Let $G(V, E)$ be a simple connected graph, with $|E| = \epsilon.$ In this paper, we define an edge-set graph $\mathcal G_G$ constructed from the graph $G$ such that any vertex $v_{s,i}$ of $\mathcal G_G$ corresponds to the $i$-th…

General Mathematics · Mathematics 2023-07-19 Johan Kok , N. K. Sudev , K. P. Chithra

Using a notation of corner between edges when graph has a fixed rotation, i.e. cyclical order of edges around vertices, we define combinatorial objects - combinatorial maps as pairs of permutations, one for vertices and one for faces.…

Combinatorics · Mathematics 2009-09-02 Dainis Zeps

In the branch of mathematics known as graph theory, graphs are considered as a set of points, called vertices, with connections between these points, called edges. The purpose of this paper is to study mappings between two graphs that have…

Combinatorics · Mathematics 2019-03-19 Jeffrey Beyerl , Cameron Sharpe

The product power throttling number of a graph is defined to study product throttling for power domination. The domination number of a graph is an upper bound for its product power throttling number. It is established that the two…

Daily internet communication relies heavily on tree-structured graphs, embodied by popular data formats such as XML and JSON. However, many recent generative (probabilistic) models utilize neural networks to learn a probability distribution…

Machine Learning · Computer Science 2024-08-20 Milan Papež , Martin Rektoris , Tomáš Pevný , Václav Šmídl
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