scholarly journals On the Isolated Vertices and Connectivity in Random Intersection Graphs

2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
Yilun Shang
Keyword(s):  
Random Graphs ◽  
Intersection Graph ◽  
Intersection Graphs ◽  
Random Intersection Graph ◽  
Probability Of Connectivity ◽  
Asymptotic Probability

We study isolated vertices and connectivity in the random intersection graph . A Poisson convergence for the number of isolated vertices is determined at the threshold for absence of isolated vertices, which is equivalent to the threshold for connectivity. When and , we give the asymptotic probability of connectivity at the threshold for connectivity. Analogous results are well known in Erdős-Rényi random graphs.

scholarly journals Component Evolution in Random Intersection Graphs

10.37236/935 ◽  
2007 ◽  
Vol 14 (1) ◽  
Author(s):  
Michael Behrisch
Keyword(s):  
Real World ◽  
Linear Order ◽  
Graph Model ◽  
Vertex Degree ◽  
Intersection Graph ◽  
Giant Component ◽  
Logarithmic Order ◽  
Intersection Graphs ◽  
Similarity Network ◽  
Random Intersection Graph

We study the evolution of the order of the largest component in the random intersection graph model which reflects some clustering properties of real–world networks. We show that for appropriate choice of the parameters random intersection graphs differ from $G_{n,p}$ in that neither the so-called giant component, appearing when the expected vertex degree gets larger than one, has linear order nor is the second largest of logarithmic order. We also describe a test of our result on a protein similarity network.

scholarly journals Epidemics on Random Graphs with Tunable Clustering

2008 ◽  
Vol 45 (03) ◽  
pp. 743-756 ◽  
Author(s):  
Tom Britton ◽  
Maria Deijfen ◽  
Andreas N. Lagerås ◽  
Mathias Lindholm
Keyword(s):  
Random Graphs ◽  
Branching Process ◽  
Intersection Graph ◽  
Epidemic Threshold ◽  
Random Intersection Graph ◽  
Large Outbreak ◽  
Process Approximation

In this paper a branching process approximation for the spread of a Reed-Frost epidemic on a network with tunable clustering is derived. The approximation gives rise to expressions for the epidemic threshold and the probability of a large outbreak in the epidemic. We investigate how these quantities vary with the clustering in the graph and find that, as the clustering increases, the epidemic threshold decreases. The network is modeled by a random intersection graph, in which individuals are independently members of a number of groups and two individuals are linked to each other if and only if there is at least one group that they are both members of.

scholarly journals RANDOM INTERSECTION GRAPHS WITH TUNABLE DEGREE DISTRIBUTION AND CLUSTERING

2009 ◽  
Vol 23 (4) ◽  
pp. 661-674 ◽  
Author(s):  
Maria Deijfen ◽  
Willemien Kets
Keyword(s):  
Power Law ◽  
Weight Distribution ◽  
Degree Distribution ◽  
Asymptotic Expression ◽  
Intersection Graph ◽  
Intersection Graphs ◽  
Random Intersection Graph ◽  
Random Weight

A random intersection graph is constructed by assigning independently to each vertex a subset of a given set and drawing an edge between two vertices if and only if their respective subsets intersect. In this article a model is developed in which each vertex is given a random weight and vertices with larger weights are more likely to be assigned large subsets. The distribution of the degree of a given vertex is characterized and is shown to depend on the weight of the vertex. In particular, if the weight distribution is a power law, the degree distribution will be as well. Furthermore, an asymptotic expression for the clustering in the graph is derived. By tuning the parameters of the model, it is possible to generate a graph with arbitrary clustering, expected degree, and—in the power-law case—tail exponent.

scholarly journals On hamiltonicity of uniform random intersection graphs

2010 ◽  
Vol 51 ◽  
Author(s):  
Mindaugas Bloznelis ◽  
Irmantas Radavičius
Keyword(s):  
Hamilton Cycle ◽  
Intersection Graph ◽  
Sufficient Condition ◽  
Intersection Graphs ◽  
Random Intersection Graph

We give a sufficient condition for the hamiltonicity of the uniform random intersection graph G{n,m,d}. It is a graph on n vertices, where each vertex is assigned d keys drawn independently at random from a given set of m keys, and where any two vertices establish an edge whenever they share at least one common key. We show that with probability tending to 1 the graph Gn,m,d has a Hamilton cycle provided that n = 2-1m(ln m + ln ln m + ω(m)) with some ω(m) → +∞ as m → ∞.

scholarly journals Degree Distributions in General Random Intersection Graphs

10.37236/295 ◽  
2010 ◽  
Vol 17 (1) ◽  
Author(s):  
Yilun Shang
Keyword(s):  
Graph Model ◽  
Intersection Graph ◽  
The Other ◽  
Intersection Graphs ◽  
Degree Of A Vertex ◽  
Random Weights ◽  
Random Intersection Graph

We study $G(n,m,F,H)$, a variant of the standard random intersection graph model in which random weights are assigned to both vertex types in the bipartite structure. Under certain assumptions on the distributions of these weights, the degree of a vertex is shown to depend on the weight of that particular vertex and on the distribution of the weights of the other vertex type.

scholarly journals Large Cliques in Sparse Random Intersection Graphs

10.37236/6233 ◽  
2017 ◽  
Vol 24 (2) ◽  
Author(s):  
Mindaugas Bloznelis ◽  
Valentas Kurauskas
Keyword(s):  
Degree Distribution ◽  
Maximum Clique ◽  
Polynomial Time Algorithm ◽  
Clique Number ◽  
Time Algorithm ◽  
Intersection Graph ◽  
Optimal Order ◽  
Intersection Graphs ◽  
Random Intersection Graph ◽  
Finite Set

An intersection graph defines an adjacency relation between subsets $S_1,\dots, S_n$ of a finite set $W=\{w_1,\dots, w_m\}$: the subsets $S_i$ and $S_j$ are adjacent if they intersect. Assuming that the subsets are drawn independently at random according to the probability distribution $\mathbb{P}(S_i=A)=P(|A|){\binom{m}{|A|}}^{-1}$, $A\subseteq W$, where $P$ is a probability on $\{0, 1, \dots, m\}$, we obtain the random intersection graph $G=G(n,m,P)$. We establish  the asymptotic order of the clique number $\omega(G)$ of  a sparse random intersection graph as $n,m\to+\infty$. For $m = \Theta(n)$ we show that the maximum clique is of size $(1-\alpha/2)^{-\alpha/2}n^{1-\alpha/2}(\ln n)^{-\alpha/2}(1+o_P(1))$ in the case where the asymptotic degree distribution of $G$ is a power-law with exponent $\alpha \in (1,2)$. It is of size $\frac {\ln n} {\ln \ln n}(1+o_P(1))$ if the degree distribution has bounded variance, i.e., $\alpha>2$. We construct a simple polynomial-time algorithm which finds a clique of the optimal order $\omega(G) (1-o_P(1))$.

scholarly journals Epidemics on Random Graphs with Tunable Clustering

2008 ◽  
Vol 45 (3) ◽  
pp. 743-756 ◽  
Author(s):  
Tom Britton ◽  
Maria Deijfen ◽  
Andreas N. Lagerås ◽  
Mathias Lindholm
Keyword(s):  
Random Graphs ◽  
Branching Process ◽  
Intersection Graph ◽  
Epidemic Threshold ◽  
Random Intersection Graph ◽  
Large Outbreak ◽  
Process Approximation

In this paper a branching process approximation for the spread of a Reed-Frost epidemic on a network with tunable clustering is derived. The approximation gives rise to expressions for the epidemic threshold and the probability of a large outbreak in the epidemic. We investigate how these quantities vary with the clustering in the graph and find that, as the clustering increases, the epidemic threshold decreases. The network is modeled by a random intersection graph, in which individuals are independently members of a number of groups and two individuals are linked to each other if and only if there is at least one group that they are both members of.

scholarly journals The Largest Component in an Inhomogeneous Random Intersection Graph with Clustering

10.37236/382 ◽  
2010 ◽  
Vol 17 (1) ◽  
Author(s):  
Mindaugas Bloznelis
Keyword(s):  
Probability Measure ◽  
Branching Process ◽  
Intersection Graph ◽  
Connected Component ◽  
Intersection Graphs ◽  
First Order ◽  
Random Intersection Graph ◽  
Vertex Set

Given integers $n$ and $m=\lfloor\beta n \rfloor$ and a probability measure $Q$ on $\{0, 1,\dots, m\}$, consider the random intersection graph on the vertex set $[n]=\{1,2,\dots, n\}$ where $i,j\in [n]$ are declared adjacent whenever $S(i)\cap S(j)\neq\emptyset$. Here $S(1),\dots, S(n)$ denote the iid random subsets of $[m]$ with the distribution $\bf{P}(S(i)=A)={{m}\choose{|A|}}^{-1}Q(|A|)$, $A\subset [m]$. For sparse random intersection graphs, we establish a first-order asymptotic as $n\to \infty$ for the order of the largest connected component $N_1=n(1-Q(0))\rho+o_P(n)$. Here $\rho$ is the average of nonextinction probabilities of a related multitype Poisson branching process.

scholarly journals Turán-type results for intersection graphs of boxes

2021 ◽  
pp. 1-6
Author(s):  
István Tomon ◽  
Dmitriy Zakharov
Keyword(s):  
Short Note ◽  
Intersection Graph ◽  
Intersection Graphs ◽  
Poset Dimension ◽  
Axis Parallel ◽  
Turán Theorem ◽  
Separation Dimension

Abstract In this short note, we prove the following analog of the Kővári–Sós–Turán theorem for intersection graphs of boxes. If G is the intersection graph of n axis-parallel boxes in $${{\mathbb{R}}^d}$$ such that G contains no copy of K t,t , then G has at most ctn( log n)2d+3 edges, where c = c(d)>0 only depends on d. Our proof is based on exploring connections between boxicity, separation dimension and poset dimension. Using this approach, we also show that a construction of Basit, Chernikov, Starchenko, Tao and Tran of K2,2-free incidence graphs of points and rectangles in the plane can be used to disprove a conjecture of Alon, Basavaraju, Chandran, Mathew and Rajendraprasad. We show that there exist graphs of separation dimension 4 having superlinear number of edges.

FUZZY INTERSECTION GRAPHS OF FUZZY SEMIGROUPS

2006 ◽  
Vol 02 (01) ◽  
pp. 1-10
Author(s):  
M. K. SEN ◽  
G. CHOWDHURY ◽  
D. S. MALIK
Keyword(s):  
Intersection Graph ◽  
Common Multiple ◽  
Intersection Graphs

Let S be a semigroup. This paper studies the intersection graphs of fuzzy semigroups. It is shown that the fuzzy intersection graph Int(G(S)), of S, is complete if and only if S is power joined. If Γ(S) denotes the set of all fuzzy right ideals of S, then the fuzzy intersection graph Int(Γ(S)) is complete if and only if S is fuzzy right uniform. Moreover, it is shown that Int(Γ(S)) is chordal if and only if for a,b,c,d ∈ S, some pair from {a,b,c,d} has a right common multiple property. It is also shown that if Int(G(S)) is complete and S has the acc on subsemigroups, then S is cyclic.

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