Finding clusters of well-connected nodes in a graph is useful in many domains, including Social Network, Web and molecular interaction analyses. From a computational viewpoint, finding these clusters or graph communities is a difficult problem. We consider the framework of Clique Matrices to decompose a graph into a set of possibly overlapping clusters, defined as well-connected subsets of vert...

Derivation of Cost Function. The projection of the joint probability distribution of the random variables X = (X1, X2, . . . , Xn), associated with the vertices in V , on a decomposable graph G is given by: pG(x) = ∏ C∈C(G) pC(xC) ∏ (C,D)∈T (G) pC∩D(xC∩D) , (1) where x is an instance in the domain of X, which we denote by X . pC(xC) denotes the marginal distribution of random variables belongin...

Let G be a connected graph on n vertices, and let ; ; and be edge-disjoint cycles in G such that (i) ; (resp. ;) are vertex-disjoint and (ii) jj + jj = jj+ jj = n, where jj denotes the length of. We say that ; ; and yield two edge-disjoint hamiltonian cycles by edge exchanges if the four cycles respectively contain edges e; f; g and h such that each of (? feg) S (? ffg) S fg; hg and (? fgg) S (...

We propose a Bayesian approximate inference method for learning the dependence structure of a Gaussian graphical model. Using pseudo-likelihood, we derive an analytical expression to approximate the marginal likelihood for an arbitrary graph structure without invoking any assumptions about decomposability. The majority of the existing methods for learning Gaussian graphical models are either re...

Finding clusters of well-connected nodes in a graph is a problem common to many domains, including social networks, the Internet and bioinformatics. From a computational viewpoint, finding these clusters or graph communities is a difficult problem. We use a clique matrix decomposition based on a statistical description that encourages clusters to be well connected and few in number. The formal ...

We answer a question of Brandstädt et al. by showing that deciding whether a line graph with maximum degree 5 has a stable cutset is NP -complete. Conversely, the existence of a stable cutset in a line graph with maximum degree at most 4 can be decided efficiently. The proof of our NP -completeness result is based on a refinement on a result due to Chvátal that recognizing decomposable graphs w...

This survey emphasises results in graph theory which were fairly difficult to prove. Because it is a personal view of the subject, this section will describe three of my own results which I personally found fairly difficult to prove (whatever their degree of difficulty in an absolute sense may be). A decomposition of a graph G is a set of subgraphs of G such that each edge of G belongs to exact...

the order graph of a group $g$, denoted by $gamma^*(g)$, is a graph whose vertices are subgroups of $g$ and two distinct vertices $h$ and $k$ are adjacent if and only if $|h|big{|}|k|$ or $|k|big{|}|h|$. in this paper, we study the connectivity and diameter of this  graph. also we give a relation between the order graph and prime  graph of a group.

This paper makes two contributions to the computational geometry of decomposable graphs, aimed primarily at facilitating statistical inference about such graphs where they arise as assumed conditional independence structures in stochastic models. The first of these provides sufficient conditions under which it is possible to completely connect two disconnected cliques of vertices, or perform th...